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TE 




662 




.A3 


WA-RD-76-14 


i no. 


AL REPORT 


' FHiWA- 




RD- 




■76-14 




v.1 


OMIC 



Dept of Transportation 




DMIC ANALYSIS OF ROA DWAY 
OCCUPANCY FOR FREEWAY PAVEMENT 
MAINTENANCE ANO REHABILITATION 




Prepared for 

FEDERAL HIGHWAY ADMINISTRATION 
Offices of Research & Development 
Washington, D.C. -20590 



This document is available to the 
public through the National Technical 
Information Service, Springfield, 
Virginia -22161 



NOTICE 



This document is disseminated under the sponsorship of 
the Department of Transportation in the interest of 
information exchange. The United States Government 
assumes no liability for its contents or use thereof. 

The contents of this report reflect the views of Byrd, 
Tallamy, MacDonald and Lewis, which is responsible for 
the facts and the accuracy of the data presented herein. 
The contents do not necessarily reflect the official 
views or policy of the Department of Transportation. 

This report does not constitute a standard, specification, 
or regulation. 



FHWA DISTRIBUTION NOTICE 



Sufficient copies of this report are being distributed 
by FHWA Bulletin to provide a minimum of one copy to 
each regional office, one copy to each division office, 
and one copy to each State highway agency. Direct 
distribution is being made to the division offices. 




Technical Report Documentation Page 



rtD- v 



1. Report No. 

\-RD-76-14 



3. Recipient's Catalog No. 



4. Title and Subtitle 

Economic analysis of 
pavement maintenance 

Vol . 1 - Final Report 



F LEEWAY 



5. Report Dote 

October, 1974 



6. Performing Organization Code 



7. Author/ s) . • 

BTC. Butlec^r. 



8. Performing Organization Report No. 



9. Performing Organization Name and Address 



rerforming Urbanization Nome and Address 

Byrd, Tall amy, MacDonald and Lewis 

Division of Wilbur Smith and Associates 
2921 Tel star Court 

Falls Church, Virginia 20590 



10. Work Unit No. (TRAIS) 

FCP-35E1012 



11. Contract or Grant No. 

DOT-FH-11-8132 



12. Sponsoring Agency Name and Address 



Sponsoring Agency Name and Address 

Office of Research and Development 
Federal Highway Administration 
U.S. Department of Transportation 
Washington, D.C. 20590 



13. Type of Report and Period Covered 



Final Report 



14. Sponsoring Agency Code 



SO 628 



15. Supplementary Notes 



FHWA Contract Manager: J. V. Boos (HRS-41) 



16. Abstract 

A program (manual and computerized) was developed to perform an economic 
analysis of premium pavements (reduced maintenance requirements). Pavement 
maintenance costs were determined in terms of impacts on motorists (users) 
and the general public (non-users) of freeways. 

Volume I - Final Report - This volume provides a complete description of the 
scope, approach, and results of evaluating the economic impact of roadway 
maintenance crew occupany, taking into account motor vehicles operating cost, 
value of time, accidents, and pollution under various freeway traffic 
conditions. The assessments and conclusions are based upon previous state- 
of-the-art and a study of field data. 

This volume is the first of a three volume series. The others in the series 
are: 



Vol. No. 

2 
3 



FHWA. No, 

76-15 
76-16 



Short Title 

Users Manual 

Program Documentation 



i7. Keywords Pavement Design, Highway Main- 
tenance, Economics, Traffic, Vehicle 
Operation Costs, Accident Cost, Value 
of Time, Pollution, Maintenance 
Models, Simulation 



18. Distribution Statement 



No restrictions. This document is avail 
able to the public through the National 
Technical Information Service, 
Springfield, Virginia 22161 



19. Security Classif. (of this report) 

Unclassified 



20. Security Classif. (of this page) 

Unclassified 



21. No. of Pages 

291 



22. Price 



Form DOT F 1700.7 (8-72) 



Reproduction of completed page authorized 



. ■ 



ACKNOWLEDGEMENT jj 

The research study covered by this report was conducted by the 
Byrd, Tall amy, MacDonald and Lewis Division of Wilbur Smith and 
Associates. The principal investigator was Bertell C. Butler, Jr. 
Others making contributions to the study included Stephen W. Hopkins 
who assisted in all phases of the study and contributed substantially 
in the development of the computer program; L. G. Byrd, who provided 
guidance in the development of the maintenance module; Robley Winfrey, 
who critiqued the approach to developing vehicle operation cost, 
and made available information on vehicle operating characteristics; 
Ross Maxwell, who directed field data gathering efforts in California, 
and other firm members who gave suggestions and provided assistance 
during the conduct of the research. 

The author wishes to thank the state highway staff members in 
California, Maryland, and Virginia for their cooperation in providing 
notice of maintenance occupancy conditions and data on traffic related 
to roadway occupancy locations. 

Special thanks are extended to Mr. James Boos of the Federal 
Highway Administration who, as project manager, provided invaluable 
assistance in contacts with Federal and State highway staff members. 

Other Federal Highway Administration personnel who made contri- 
butions to the study include Tom Pasko and Dick McComb, Office of 
Research and Development; Ed Evans, Richard Murphy and James Robertshaw, 
Computer Services Division, and Perry Kent, Program Management Division. 



n 



PREFACE 



Report Contents 

"An Economic Analysis of Roadway Occupancy for Freeway Pavement 
Maintenance and Rehabilitation" is contained in three volumes. This 
is the result of work accomplished under a Federally Coordinated Research 
Program, Project 5E, Premium Pavements for "Zero Maintenance," during 
the period of July 1973 to May 1975. 

Volume I, Final Report, provides a complete description of the 
scope, approach, and results of evaluating the economic impact of 
roadway maintenance crew occupancy, taking into account motor vehicle 
operating cost, value of time, accidents, and pollution under various 
freeway traffic conditions. The assessments and conclusions are based 
upon previous state-of-the-art and study of field data. 

Volume II, Users Manual, presents the results of the study as a 
users manual with a systems approach to pavement design, which evaluates 
environmental, operational performance and serviceability factors for 
alternative pavements under a variety of rehabilitation and maintenance 
strategies. The presentation is in two parts: The first is the 
Algebraic Users Manual, for hand computations. The second is the User 
Manual for Program EAROMAR (Economic Analysis for Roadway Occupancy for 
Maintenance and Rehabilitation) which gives a detailed description 
of the format and coding for all required input and a general description 
of the optional input to modify the impacts for local needs. 

Volume III, Program Documentation, contains a complete description 
of the internal variable and computations for the computer program 
EAROMAR, and thus is the basis for any future program modifications. 
The format and coding for all inputs are described in detail. One 
change to the program has been made by FHWA, which is documented in 
this Volume. This modification incorporates an inflation rate of 10 
percent in present worth computations. 

Report Applications 

High traffic volumes, heavy loads, and weathering on existing 
pavement designs cause accelerated damage and early deterioration. 
Maintenance operations required to keep these highway facilities service- 
able create a conflict with the motorist causing delays, and increasing 
pollution and accident opportunities. These repairs are: (1) costly 
due to the extensive traffic control required, (2) limited to between 
peak hour periods to avoid exceeding the traffic volume capacity, and 
(3) difficult to perform and often temporary due to problems in mobilizing 
the work crew. Thus the elimination of these impacts results in reduced 
highway maintenance expenditures and higher levels of safety, economy 
and convenience to the user. 



m 



The FHWA has determined that one solution to the difficulties 
associated with highway maintenance operations is to produce a "pre- 
mium pavement" which reduces maintenance requirements. The savings 
derived from direct maintenance expenditures and motorist costs over 
the life of the pavement could be invested in constructing a "premium 
pavement" as compared to existing designs. 



TV 



TABLE OF CONTENTS 



PAGE 

ACKNOWLEDGEMENT ii 

PREFACE 

m 

INTRODUCTION 1 

Scope 2 

Existing Maintenance Models 3 

Approach 7 

HIGHWAY MAINTENANCE MODULE 11 

Maintenance Workload Models 11 

Pavement Patching 13 

Blowups 27 

Mudjacking 29 

Joint Sealing 37 

Crack Sealing 38 

Bituminous Base and Surface Repair 39 

Composite or Overlayed Concrete Pavement 40 

Workload Program Modifications 40 

Axle Loading Modification to Maintenance Workload Models 42 

Work Requirements 53 

Simulation Process 54 

Worksite 55 

Size of Worksite 56 

Simulation Iterations 57 

Spacing 57 

Full Depth Concrete Patch Distribution 58 

Partial Depth Concrete Patch Distribution 60 

Performance Standards 64 

MOTORIST MODULE 72 

Speed 80 

Instrumentation 80 

Field Study 82 

Data Reduction 86 

Speed Profiles 87 

Traffic Zone Assumptions 94 



TABLE OF CONTENTS (Cont.) 



PAGE 



Queue Assumptions 96 

Highway Average Speed 101 

Queue Delay ' 107 

Traffic 111 

Distributions 111 

Volume 114 

Vehicle Parameters 117 

Operation Costs 120 

Fuel Consumption Models for Vertical Alignment 121 

Fuel Consumption Models for Horizontal Alignment 124 

Alignment Weight Factor 130 

Speed Changes 134 

Speed Change Weight Factor 140 

Alignment Models for Tire Wear 141 

Speed Change Model for Tire Wear 149 

Alignment Models for Oil Consumption 153 

Speed Change Models for Oil Consumption 158 

Alignment Models for Maintenance Costs 163 

Speed Change Models for Maintenance Costs 169 

Depreciation Model 174 

Value of Time 180 

Commercial Vehicles 180 

Passenger Cars 180 

Accidents 183 

Influence Zone Accidents 183 

Speed Change Accidents 183 

Accident Costs 185 

Pollution 187 

SUMMARY 193 

RESULTS 211 

REFERENCES 214 



VI 



TABLE OF CONTENTS (Cont.) 

PAGE 

APPENDIX A - Field Data Collection 219 

APPENDIX B - Vehicle Consumption Tables 237 

APPENDIX C - Value of time tables 257 

APPENDIX D - Glossary 263 

APPENDIX E - Selected Bibliography 266 



vn 



LIST OF FIGURES 
Number Page 

1 Regression curves for man-hours spent on patching 

on test sections included in 14-1 study 19 

2 Regression curves for total patching expenditures 

on test section included in 14-1 study 20 

3 Regression curves for material patching expenditures 

on test section included in 14-1 study 21 

4 Patching curves for bituminous concrete pavements 25 

5 Patching curves for port! and cement concrete 

pavements 26 

6 Example of blowup histories in Michigan and Iowa 
compared with model selected for program 28 

7 Example of documented hours of blowup occurrence 

based on Illinois study 31 

8 History of mudjacking as recorded in a Michigan 

Study by Oehler and Hoi brook 33 

9 Curve fit to mudjacking expenditures as reported 
by the Ohio Turnpike after conversion to 1967 

dollars 36 

10 Typical performance curves for sections of the 
Illinois Toll Road where the failure age based on 
AASHO computation would have been 61, 58, 75, and 

114 years 43 

11 Schematic of psi, axle loading and null transfer 
options available to pavement systems design program 
in accessing program EAROMAR, Economic Analysis of 
Roadway Occupancy for Maintenance and Reconstruction 51 

12 Frequency distribution developed for full depth 
concrete patching 61 

13 Frequency distribution developed for partial depth 
concrete patching 63 

14 Typical maintenance performance standard 65 



vm 



LIST OF FIGURES (Cont.) 
Number Page 

15 Four, three and two lane closures on an eight-lane 
freeway 74 

16 One-lane closure and a four-lane closure and 
crossover on an eight-lane freeway 75 

17 Three, two and one lane closure, together with 

a crossover for a six-lane freeway 76 

18 Two and one lane closure together with a crossover 

for a four-lane freeway 77 

19 All directional lanes closed and a detour used for 
traffic 78 

20 Schematic of the test frequency generated by the 
oscillator box 81 

21 Schematic of the low frequency speedometer signal 83 

22 Schematic of the high frequency event marker signal 84 

23 Schematic of signals generated on the cassette tape > 
during a typical test vehicle profile run through 

a work zone 85 

24 Speed profiles developed between 1 and 2 P.M. on an 
eight-lane freeway where two out of four lanes were 
closed to traffic in the P.M. peak direction 90 

25 Speed profiles developed between 11 A.M. and 1 P.M. 
on a six-lane freeway where two out of three direc- 
tional lanes were closed to traffic in the P.M. peak 
direction 91 

26 Speed profiles developed between 2 and 3 P.M. on a 
six-lane freeway where two out of three directional 
lanes were closed to traffic in the P.M. peak direc- 
tion 92 

27 Speed profiles developed between 5 and 7 P.M. 

on a four-lane freeway where one out of two direc- 
tional lanes were closed to traffic in the P.M. 
peak direction 93 

ix 



LIST OF FIGURES (Cont.) 
Number Page 

28 Schematic speed profile of unqueued traffic 

operation through a traffic control zone 95 

29 Example of a queue on a four-lane freeway 97 

30 Example of a queue on a four-lane freeway 98 

31 Schematic speed profile of traffic operation 
through a traffic control zone on the verge of 

queuing 99 

32 Schematic speed profile of traffic operation through 

a traffic control zone where a queue has occurred 100 

33 Relationships between design speed and capacity 102 

34 Speed curves for highway designs of 70, 60, and 

50 mph where speed limit equals design speed 104 

35 Speed curves for a range of speed limits on a road 

with a 70 mph design speed 105 

36 Demand and capacity relationships where a queue is 
created 108 

37 Relationship between queue delay, capacity and 

demand volume 109 

38 Hourly distributions of traffic by trip purpose and 
direction developed for use as defaults in program 112 

39 Distribution of "All Traffic" in the AM peak 
direction 115 

40 Distribution of "All Traffic" in the PM peak 
direction 116 

41 Price trend of commercial vehicles over a ten-year 
period (1972 Automobile Facts and Figures, Motor 
Vehicle Manufacturers Association) 119 

42 Vertical alignment gasoline consumption curves 

for basic passenger car 125 

43 Gasoline Consumption Curves for horizontal curves 

in 2 degree increments for basic passenger car 132 



LIST OF FIGURES (Cont.) 
Number Page 

44 Excess gasoline consumption for speed reductions 
for a series of initial speed curves for basic 
passenger car 139 

45 Vertical alignment tire wear curves for basic 
passenger car 143 

46 Horizontal alignment tire wear curves for basic 
passenger car 145 

47 Excess tire wear for speed reduction for a series 

of initial speed curves for basic passenger car 151 

48 Vertical alignment oil consumption curves for 

basic passenger car 154 

49 Excess oil consumption for speed reductions for 
a series of initial speed curves for basic 

passenger car 160 

50 Vertical alignment maintenance costs curves for 

basic passenger car 166 

51 Annual vehicle miles as a function of speed 177 

52 Depreciation rate for a range of vehicle weights 

as a function of speed 179 

53 Trend of operation costs for commercial vehicles 

over an eight-year period 181 

54 Pollution adjustment factor for CO emissions 188 

55 Pollution adjustment factor for HC emissions 189 

56 Broad program flow of EAROMAR showing the relation- 
ship between program blocks and the pavement design 
systems program 194 

57 A flow diagram of the initialization block of 
program EAROMAR which includes subroutines INITAL, 
OPPARA and RPRINT 196 

58 A flow diagram of the design interfacing block of 
program EAROMAR which is called subroutine YEAR 200 



XI 



LIST OF FIGURES (Cont.) 
Number Page 

59 A flow diagram of the maintenance block of 
program EAROMAR which is a subroutine named 

MAI NT 204 

60 A flow diagram of the motorist block of program 
EAROMAR which is a subroutine named MOTOR ' 207 

61 Circuit diagram of frequency box attached to 
speedometer cable of test car 220 

62 Example of the field data logs and summaries kept 

by the field teams 223 

63 Lane closure diagram of observation site number 1, 
1-95, Prince William County, Virginia 224 

64 Lane closure diagram of observation site number 2, 
1-95, Prince William County, Virginia 225 

65 Lane closure diagram of observation site number 3, 
1-95, Stafford, Virginia 226 

66 Lane closure diagram of observation site number 4, 
1-95, Stafford, Virginia 227 

67 Lane closure diagram of observation site number 5, 
State Highway 17, Oakland, California 228 

68 Lane closure diagram of observation site number 6, 

(1st closure), U. S. 101, San Mateo, California 229 

69 Lane closure diagram of observation site number 6, 

(2nd closure), U. S. 101, San Mateo, California 230 

70 Lane closure diagram of observation site number 7, 
State route 92, San Mateo, California 231 



xn 



LIST OF TABLES 
Number Page 

1 Stepwise Regression Models Developed for Man-hours, 
Total Costs and Material Costs for the Combined 
Activities Patching and Maintenance Resurfacing 

for Bituminous Sections 16 

2 Stepwise Regression Models Developed for Man-hours, 
Total Costs and Material Costs for the Combined Activi- 
ties Patching and Maintenance Resurfacing for Concrete 
Sections 17 

3 Stepwise Regression Models Developed for Man-Hours, 
Total Costs and Material Costs for the Combined 
Activities Patching and Maintenance Resurfacing 

for all Pavement Sections 18 

4 Logit Models for Pavement Patching 24 

5 Blowups as reported in various studies 30 

6 Annual mudjacking expenditures on the Ohio Turnpike 
adjusted to 1967 dollars 34 

7 Joint sealing material conversion 38 

8 Pavement serviceability relationships based on Illinois 
Toll Roads studies 45 

9 Equivalent 18-kip single axle loads per thousand 
vehicles 52 

10 Typical hourly labor rates, equipment rental rates, 

and material unit costs 68 

11 Activity performance standards developed for an 
economic analysis of roadway occupancy for maintenance 
and rehabilitation 70 

12 Maintenance Activity Performance Standard Data used as 
defaults in the program 71 

13 Example of computer generated speeds developed from 
field tapes 88 

14 Computer printout of computed hourly volumes at a 

test site used to develop speed profiles 89 



xm 



LIST OF TABLES (Cont.) 
Number Page 

15 Computer generated speed matrix for an eight-lane 
freeway 106 

16 Summary of truck data developed from computer printout 
developed by FHWA from the U.S. 1972 Truck Weight 

Study 118 

17 Regression statistics for vertical alignment fuel 
consumption models for passenger cars 123 

18 Regression statistics for horizontal alignment fuel 
consumption models for passenger cars 127 

19 Regression statistics for horizontal alignment fuel 
consumption model coefficients for passenger cars 129 

20 Passenger car gasoline consumption in gallons per 

hour per vehicle 131 

21 Ratio of gasoline consumption per vehicle hour to 
passenger car consumption for a range of vehicle 

weights on level tangent sections 133 

22 Regression statistics for weight ratio models for 
passenger car gasoline consumption on tangent 

sections 135 

23 Regression statistics for the A and B coefficients 

r r 

in the weight ratio model set for gasoline consumption 136 

24 Regression statistics for speed change models for 
passenger car excess gasoline consumption per cycle 138 

25 Regression statistics for horizonta; and vertical 
alignment models for passenger car tire wear and 

the horizontal alignment set intercept A. 142 

26 Regression statistics for level tangent section models 

for a range of vehicle weights for tire wear 147 

27 Model predicted tire wear by vehicle weight class and 
ratio of tire wear per vehicle per hour to passenger 

car tire wear for a range of vehicle weights 148 



xiv 



LIST OF TABLES (Cont.) 
Number Page 

28 Regression statistics for speed change models for 
passenger car excess tire wear per cycle and for 

the resulting model coefficient models 150 

29 Ratio of excess tire wear for vehicle weights 
5-, 12-, and 50-kips to passenger cars at 4-kips 

for a 40 mph speed change cycle 152 

30 Ratio of oil consumption per vehicle per hour to 
passenger car consumption for a range of vehicle 

weights for level tangent sections 156 

31 Regression statistics for vehicle oil consumption 

weight ratio models 157 

32 Regression statistics for speed change models for 
passenger car excess oil consumption per cycle 159 

33 Ratio of excess oil consumption for vehicle weiqhts 
of 12-, 40-, and 50-kips to passenger cars at 4-kips 

for a 40 mph speed change cycle 162 

34 Regression statistics for vertical alignment models 

for passenger car maintenance costs 164 

35 Ratio of maintenance cost per vehicle per hour to 
passenger car cost for a range of vehicle weights for 
level tangent sections 167 

36 Vehicle maintenance costs weight ratio models 168 

37 Regression statistics for speed change models for 
passenger car excess vehicle maintenance cost and 

the intercept A for the model set 171 

38 Ratio or tire wear for vehicle weights 5-, 12-, 40-, 
and 50-kips to passenger cars at 4-kips for 40 mph 

speed change cycle 172 

39 Vehicle maintenance weight ratio models 173 

40 Annual vehicle mileage related to vehicle speed 176 



xv 



LIST OF TABLES (Cont.) 
Number Page 

41 Constants of influence zone annual accidents 

equations taken from NCHRP Report 47 184 

42 Regression statistics for CO and HC emission 

adjustment factors as a function of speed 190 

43 Summary of program default components and input 
requirements and options for each of the program 
functions performed by the initialization block 

of program EAROMAR 197 

44 Summary of program default components and input 
options for each of the program functions performed 

by the design interfacing block of program EAROMAR 201 

45 Summary of program default components and input 
options for each of the program functions performed 

by the maintenance block in program EAROMAR 205 

46 Summary of program default components and input 
options for each of the program functions performed 

by the motorist block in program EAROMAR 208 

47 Required input as specified for 6 different pavement 
types in demonstration runs of the program EAROMAR 212 



48 Results for 6 different pavement types in demonstration 
runs of the program EAROMAR 



213 



49 Fuel, tires, oil, maintenance and depreciation in 
gallons, .001 inches, quarts, dollars and percent, 
respectively per vehicle hour for level tangent 

sections 238 

50 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for tangent sections with +1% grade 239 

51 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for tangent sections with +2% grade 240 

52 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for tangent sections with +3% grade 241 



xvi 



LIST OF TABLES (Cont.) 
NUMBER Page 

53 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for tangent sections with +4% grade 242 

54 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for tangent sections with +5% grade 243 

55 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for tangent sections with +6% grade 244 

56 Fuel, tires, oil maintenance in gallons, .001 inches, 
quarts and dollars respectively per vehicle hour for 
tangent sections with -1% grade 245 

57 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle hour 
for tangent sections with - 2% grade 246 



> 



58 Fuel, tires, oil and maintenance in gallons, .001 inches 
quarts and dollars respectively per vehicle hour for 
tangent sections with -3% grade 247 

59 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for tangent sections with -4% grade 248 

60 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for tangent sections with -5% grade 249 

61 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for tangent sections with -6% grade 250 

62 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle hour 
for level sections with 1 curvature 251 

63 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for level sections with 2 curvature 252 

64 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for level sections with 3 curvature 253 

xvii 



LIST OF TABLES (Cont.) 
Number Page 



65 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 
hour for level sections with 4 curvature 



254 



66 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for level sections with 5 curvature 255 

67 Fuel, tires, oil and maintenance in gallons, .001 
inches, quarts and dollars respectively per vehicle 

hour for level sections with 6 curvature 256 

68 Benefits of time savings for school trips in dollars 

per person 258 

69 Benefits of times savings for personal -business trips 

in dollars per vehicle 259 

70 Benefits of time savings for social -recreational trips 

in dollars per vehicle 260 

71 Benefits of time savings for vacation trips in dollars 

per vehicle 261 

72 Benefits of time savings for work trips in dollars 

per person 262 



xvm 



INTRODUCTION 

Existing pavement design on freeways is subject to accelerated 
deterioration due to weathering, heavy loads and high traffic volumes. This 
deterioration creates a need for maintenance early in the life of the pavement 
and results in disruption of traffic by maintenance occupancy forces. Such 
maintenance is costly due to the extensive traffic control needed to protect 
both maintenance crews and motorists. Scheduling of these occupancy periods 
must occur during off peak hours to avoid exceeding volume capacity. Also, 
maintenance crew job site movements are hampared by limited access and high 
traffic speeds. Maintenance performed under these conditions must frequently 
be repeated because limited time results in temporary or hasty repairs which 
are costly. These occupancy periods also cause conflicts with the motorist 
and in turn affects motorist operating costs, delays and increases potential 
for accidents. Finally, the general slowing of traffic generates increased 
levels of pollution. The elimination of these costs and impacts can result 
in reduced highway maintenance expenditures and higher levels of safety, 
economy and convenience to the highway user. 

One means of minimizing these difficulties associated with freeway 
maintenance is to produce a pavement, which can be referred to as a "premium 
pavement," requiring less maintenance or no maintenance. This subsequent 
reduction in direct maintenance activities will in turn reduce maintenance 
expenditures, motorist costs, i.e., operation, time, and accidents. These 
savings could justify the increased costs of constructing this, so called, 
"premium Pavement." 

1 



An adequate economic analysis of the cost of maintenance, rehabilitation 
and motorist impacts as they relate to a "premium pavement" must take into 
consideration the relationship of a multitude of quantifiable costs for a wide 
range of pavement design strategies and therefore a systems approach appears 
proper. The systems approach accomplishes this through allocation of present 
and future cash flow which are quantified and converted to present worth in 
evaluating a range of pavement design strategies over a pavement's life. A 
wide range of pavement designs and maintenance strategies have been acknowledged 
to exist among the 50 State highway departments and therefore the objective 
sought in this research effort were directed primarily to developing motorist 
costs common to all States. 

Specifically, the objective of this project was the development of 
motorist-related data inputs for currently available systems analysis models 
for pavement design as a preliminary effort in the development of economic 
warrants for the use of premium pavements. The economic analysis will 
encompass vehicle operating costs, delays to drivers and passengers, air 
pollution, and accidents related to maintenance operations. 

Scope 

This study was to draw on existing system analysis models which could be 
used for analyzing highway maintenance, but any model selected was to be modi- 
fied as necessary to insure that it is easily adaptable to the needs of the 
50 State highway departments. 

The maintenance predicted in the model was to be limited to activities 
related to rigid and flexible pavement systems. Information identified 



as being relevant to the model included highway vertical and horizontal 
alignment, vehicle trip purpose and occupant income level, speed profiles, 
traffic volume, traffic composition and hourly distribution, accidents, 
detour lengths, and lane closure configurations. 

The model was to accommodate 4-, 6-, and 8- lane freeways. In the 
determination of values for time, the use of the procedure and information 
provided in the SRI research report "The Value of Time Saved by Trip Purpose," 
(27) was incorporated into the study. 
Existing Maintenance Models 

Two formal literature searches were made to identify system models 
related to pavement maintenance. One search was through the Highway Research 
Information Service and the second was through the National Technical Infor- 
mation Service. 

The principal system analysis models for pavements which were identified 
as presently being developed were the following: 

A. The Texas Transportation Institute, University of Texas and 
Texas Highway Department, Judson, McCullough, et al . (1-10) 

B. The Massachusetts Institutes of Technology, Moavenzadeh, et al. (11-19) 

C. The Australian Commonwealth, Brueau of Roads, Both, Lock, Delaney, 
et al. (20) 

D. The Ontario Department of Transportation and Communications, Phang, 
et al. (21-25) 

Each of these models address highway maintenance and rehabilitation to 
some degree. Other pavement design systems have been reported which consider 



rehabilitation but not maintenance. All of these studies have been reviewed 
and evaluated by one or another of the above-listed agencies in connection 
with their system analysis models. 

The Texas group has given major emphasis to evaluating roadway occupancy 
impact on the user as part of the total economic evaluation of roadway design. 
However, the impact is limited to rehabilitation occupancy. The rehabilitation 
cycles are based on pavement performance predictions to some specified minimum 
present serviceability rating. Both the initial design and the rehabilitation 
design are considered in the analysis. The prediction of a terminal Pavement 
Serviceability Index (PSI ) involves the evaluation of projected traffic load- 
ings and the subgrade condition for a given pavement design. Maintenance 
requirements are based on the model presented in NCHRP-42 (26). The model 
predicts total annual pavement and shoulder maintenance requirements as a 
function of pavement age and days of freezing weather. 

The MIT group has emphasized the uncertainties and variabilities 
associated with the physical characteristics of a pavement system and of the 
environment to which the pavement is subjected. These uncertainties, expressed 
in terms of probabilistic distributions, are used in a series of analytical 
models to predict three modes of damage progression (rut depth, slope variance, 
cracking) over time for various pavement designs. A probability distribution 
for the pavement condition (PSI), in terms of the AASHO present serviceability 
equation, is determined using predictions of the three damage parameters and 
their computed variances. This distribution is used in the computation of PSI 
value on an annual basis. 



Polynominal regressions were computed for the data developed in the AASHO 
road test to produce equations which predict mean rut depth and the area of 
patching and cracking as a function of PSI. The MIT model predicts maintenance 
requirements as a function of these two damage components. The patching quan- 
tity is based on the difference between the patching and cracking areas pre- 
dicted in two adjacent years. It also is related to a maintenance level which 
specifies the percent of available patching which will be done. Similar 
assumptions are made for sealing the patching and cracking area. Also, 
assumptions are made on filling ruts with patching material. 

The MIT group assumes a direct relationship between the level of main- 
tenance and the pavement condition (PSI) and adjust each year's predicted 
PSI through a feedback process. 

The quantity of maintenance is costed using standardized estimates of 
labor, equipment and material for each unit of maintenance required. 

The work done in Australia was directed toward evaluating the conse- 
quences of alternate road improvements and therefore is a highway economic 
evaluation model. However, the maintenance for pavement surfaces is modeled 
as a function of the age of the sealed surface, the surface area and traffic. 
The model is based on historical records of actual maintenance cost on well- 
maintained roads together with estimates of typical surface age and traffic. 

The pavement model system presented by Ontario mentions the necessary 
elements, i.e., delay cost to user associated with resurfacing and maintenance 
and maintenance costs. The delay costs are not used but reference is made 
to work done by the Road Research Laboratory. Maintenance costs are assumed to 



increase with pavement age and only rough estimates were used in examples of 
the model . 

Most of the models reviewed concentrate on predicting resurfacing cycles 
over the life of the pavement based on some measure of service to the user. 
Only Texas included an analysis of user cost associated with rehabilitation. 
MIT has the only model to predict specific maintenance requirements, i.e., 
patching, sealing, rut filling. Further, these quantified requirements are 
related to the pavement design. The other models predict general surface 
maintenance and apply to any high-type pavement surface. 

It was concluded that none of the existing models would satisfy the 
objectives sought in this project. The existing models, with the exception 
of the MIT model, predict a single all-encompassing pavement maintenance 
requirement, usually in monetary terms. The MIT model predicts patching for 
bituminous pavements only and as a function of the pavement's present 
serviceability index. 
Approach 

An effective evaluation of the economic impact of roadway occupancy on 
the highway motorist requires a good estimate of the magnitude of work required 
by the maintenance forces over the life of the pavement. This estimate should 
embrace quantified estimates of workload for a range of activities. Further, 
the work required must be translated into hours of required roadway occupancy. 

The forecast of workload should be related to the pavement design, its age 
and the factors it will be subjected to over its life. These include traffic 
loadings, climatic factors and maintenance levels. 



Without detailed models, the only analysis possible is that between gen- 
eral levels of maintenance, i.e., existing maintenance levels versus no main- 
tenance or a percent reduction in existing overall levels. As envisioned, the 
approach most likely to be taken in developing a premium pavement is to consi- 
der how to eliminate or reduce specific maintenance activities. For example, 
eliminate blow-ups or joint sealing or pavement patching. If the savings in 
maintenance and user costs exceeds the increased construction costs associated 
with the premium pavement which eliminates the maintenance, then an economic 
warrant for the construction of the premium pavement has been established. 

Data or models permitting the prediction of annual levels of specific 
pavement maintenance activity do not exist. However, many highway agencies 
are presently in the process of developing or implementing either or both 
pavement management and maintenance management systems. In the future, 
these systems can be expected to generate the data needed to develop the 
required maintenance activity models sought for this project. 

Until these models are available, a series of interim models will be 
developed. These will be based on available, though limited data, but will 
allow for the development of a comprehensive structuring of a systems analysis 
model for predicting maintenance requirements. 

Once an annual workload has been predicted for an activity, it must be 
translated into specific hours of roadway occupancy. These hours of roadway 
occupancy determined needed to be established in terms of the days of each 
hour of occupancy. These hours will vary widely between State agencies, 
depending on a number of factors, which include: 



1. The time spent at each worksite 

2. The net hours of continuous time available for closing lanes of 
the freeway 

3. The hours that a work crew is permitted to work 

4. The length of the roadway work zone and the concentration 
of work within the work zone. 

It was determined that variations in these factors could be handled by 
allowing them to be input into a program which would simulate the performance 
of work on the roadways. In this way the hours of roadway occupancy determined 
would be responsive to local practices and changes over time could readily be 
accumulated to update the program. 

Individual agencies can make use of activity performance standards to 
develop productivity rates at worksites and to cost the activity. 

The economic impact of a roadway closure on the highway motorist 
includes an evaluation of the change in: 

1. Vehicle operation costs 

2. Time costs 

3. Accident costs 

4. Pollution levels. 

For a given roadway, vehicle operation costs will be a function of speed, 
speed changes, traffic volume and composition. A data collection program was 
planned and implemented to develop data on speeds and speed changes at main- 
tenance worksites on 4-, 6-, and 8-lane freeways. This data was used in the 
development of models which could be used to predict vehicle average speeds 



under a variety of roadway lane closure conditions. Traffic volumes must be 
specified by the user of the economic analysis developed in this study. 
Traffic composition is built into programming developed for the analysis but 
can optionally be specified by the user. 

The vehicle operation parameters which make up vehicle operation costs 
are principally: 

1. Fuel consumption 

2. Tire wear 

3. Oil consumption 

4. Maintenance expenses 

5. Depreciation. 

To insure that the program being developed for the economic analysis 
of roadway occupancy for maintenance and reconstruction could be readily 
updated, each of the five operation parameters was modeled. In this way 
current unit costs inputs for fuel, tires, oil, maintenance, and vehicles 
could be used in the analysis. 

The study scope required that the time costs be evaluated using the pro- 
cedures developed by SRI (27). This requires traffic volume information by 
trip purpose. To accommodate this requirement, it was decided that an hourly 
volume matrix defining the following seven trip purposes would be incorporated 
into the program by roadway direction: 

1 . Work trips 

2. Personal business trips 

3. Social recreation trips 



4. School trips 

5. Vacation trips 

6. Commercial vehicle trips 

7. Total trips. 

The value of time routine developed by SRI also requires a measure 
of the increment of time loss per vehicle. This is based on the average 
time loss associated with all vehicles in a given hour of the day. 



10 



HIGHWAY MAINTENANCE MODULE 

Maintenance Workload Models 

One of the sources of data used for developing models for this 
project was developed in conjunction with NCHRP Report No. 42 v " - 
In this NCHRP study No. 14-1, maintenance activity data was developed 
by the consultant on 28 sections of interstate highways in five regions 
of the country. Seven different categories of pavement maintenance 
were specifically identified and reported on by personnel working for 
each of the agencies maintaining the sections. A form developed by the 
consultant was used for reporting and the reported information was 
thoroughly screened and validated to insure its accuracy. Therefore, 
it was felt that this information could be relied on in developing 
models or relationships. 

The reporting form developed by the consultant accounted for man- 
hours by class of labor, equipment hours or mileage (as was appropriate) 
for a range of equipment classifications, and the quantity of material 
and its unit cost. The accounts established for the purpose of collect- 
ing data on the maintenance of pavements were defined as follows: 
A. Routine Roadway Surface Operations 

1. Patching -- All permanent and temporary patching on both 
concrete and bituminous pavements- 

2. Joint and crack filling -- All work associated with joint and 
crack filling of a pavement including cleaning and cutting 
wells not including any work associated with the edge crack 

11 



between the pavement and the shoulder which should be 
charged to another account number. 
3. Other costs -- All routine work done on the pavement surface 
which is not included under Items 1 and 2. 
B. Special Roadway Surface Operations 

1. Mudjacking and undersealing -- All work associated with rais- 
ing concrete slabs by pumping material under the slab or any 
work associated with filling voids under either rigid or flex- 
ible type pavements regardless of the type of material used. 

2. Bituminous treatment -- All work where bituminous liquids are 
placed on a pavement surface not including joint or crack 
filling and regardless of whether aggregates are used to 
cover the bituminous liquid. Covering excess bituminous 
materials with sand or aggregate also is included under 

this item. 

3. Resurfacing (bituminous less than 3/4" thick) -- All work where 
a bituminous mix is used on pavement surface not including 
items normally included under patching and where final thick- 
ness of the bituminous material does not exceed 3/4". 

4. Other costs -- All special work done on the pavement surface 
which is not included under items 1, 2 3 and 3. 

The data which was summarized from the daily reports developed 
for the NCHRP 14-1 study for each of the above delineated activities 
was tabulated by man-hours. An examination of the total man-hours 
associated with each activity revealed the following distribution of 

12 



work. Under A-l, patching, 57.2% of the total man-hours were invested. 
Under A-2, sealing joints, 26.7% of the total man-hours were invested. 
Therefore, for all pavement types, these two categories accounted for 
approximately 84% of the total investment in man-hours. Other categor- 
ies where extensive work was reported included B-l, mudjacking and 
undersealing, where 13% of the man-hours invested in these sections was 
expended. For the overlay and bituminous sections, 26.7% of the man- 
hours were invested in Item B-2, bituminous treatment. The remainder 
of the activity on the sections monitored in the NCHRP study were in- 
vested in maintenance resurfacing and in the "other" cost account 
categories, A-3 and B-4. 

The only maintenance activity data common to essentially all test 
sections in the 14-1 study was the pavement patching. The other activi- 
ties were scattered randomly to sections and therefore could not be used 
as a basis for model development. They were useful in providing a sub- 
jective assessment of the relative weightings to be associated with 
each activity in the total maintenance requirement. 

Pavement Patching 
The major pavement maintenance activity is pavement patching. This 
is revealed in the above statistics. Therefore, a comprehensive analy- 
sis was made of data available from 14-1 for the purpose of developing 
pavement patching models. The data was examined in three groups and 
three investment categories. The groups were concrete pavements, bitumi- 
nous and overlay pavements, and all pavements. The categories were man- 
hours, total costs, and material cost. A series of independent variables 

13 



which were thought to have a possible influence on the magnitude of 
pavement patching were identified. These variables were as follows: 

1. Average annual daily traffic volume per lane 

2 

2. Pavement age and age 

3. 18-kip axle loadings per lane 

4. Accumulated 18 kip axle loadings per lane over the life of 
the pavement (life being pavement age) 

5. Number of days when the maximum daily temperature was below 
32°F 

The selection of these variables was based on the original analyses 
made of the total data where a single pavement model for three pavement 
types was developed and the total pavement maintenance requirement was 
found to be a function of the pavement's age squared and the number of 
days when the maximum temperature was below 32°F. The dependent varia- 
bles examined in conjunction with each of these identified independent 
variables were man-hours per lane mile, material costs per lane mile, 
and total cost per lane mile (labor + equipment + material). 

A series of stepwise multiple regression analyses were made on 
each group and category. The most significant variable to be identified 
was age. The number of days when the temperature was below 32°F was 
the second variable selected in the stepwise regression but its signifi- 
cance level was quite marginal. 

An examination of the residuals, from the analyses with age squared 
being the independent variable, suggested that two of the sections in- 
cluded in the analysis were out of line with the other sections. A 

14 



study of the characteristics of these two sections, based on their des- 
cription in the NCHRP Report No. 42, revealed that both had unusually 
poor subgrades and therefore extraordinary high maintenance requirements 
It was determined that this was a suitable basis for eliminating these 
two sections from the analysis. 

The independent variables were restructured to include average 
annual traffic, age, age squared, age cubed, and the number of days 
when the maximum temperature was below 32 F. Further, a terrain fac- 
tor was added to reflect flat through mountainous terrain. Arbitrary 
values of 1 through 5 were given to flat to mountainous terrain respec- 
tively. 

In the series of stepwise multiple regressions, age cubed was 
identified as the most significant variable at the Step 1 level, fol- 
lowed by either age squared or age and then ADT or terrain. The ADT 
and terrain factors were not considered significant. In the conduct 
of the analysis a few modifications were made to the terrain factor 
and a series of ages between age squared and age cubed were also exam- 
ined. The resulting models and their regression statistics are 
shown in Table 1 for the bituminous sections and Table 2 for the con- 
crete sections and in Table 3 for all sections combined. 

Assumptions were made as to ADT and terrain and for a range of 
ages, and values were computed for each of the regression models and 
plotted. These were compared with actual plots of the data from the 
NCHRP 14-1 study. Typical curve sets are illustrated in Figures 1-3. 
It was determined that neither the terrain nor the ADT factor 

15 



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10 
AGE (YEARS) 



15 



20 



Figure 1. Regression curves for man-hours spent on ,„,, 
patching on test sections included in 14-1 study ' 



19 



(ft 

< 
_l 
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Q 



tu 



Z 
< 



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= 500- 



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Figure 2. Regression curves for total patching 
expenditures on test section included in 
14-1 study (26) 

20 



I200T 



CO 

or 

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1000- 




10 
A6E( YEARS ) 



Figure 3. Regression curves for material patching 



expenditures on test section included in 14-1 study: 



(26) 



21 



contributed significantly to explaining the maintenance patching re- 
quirement and therefore these two variables were dropped, leaving just 
the age. 

The shape of the curve, which suggests fairly high maintenance 
expenditures in the early years, was not deemed realistic. As may be 
noted in Figures 1-3, the actual data covered a span between the 
three-year old and ten-year old pavement. Therefore, the portion of 
the curve prior to age three was based on no data. Other than con- 
struction deficiencies, which realistically should not be considered 
maintenance, there should be no patching expenditures required for a 
new pavement. Therefore, an assumption that the level of expenditures 
is zero when age is zero seemed reasonable. Further, the extrapolation 
of the regression curves beyond ten years produces expenditures that are 
enormous and there was no data to validate the indefinitely increasing 
accelerated rate of maintenance expenditures with time. Therefore, it 
was determined that a reasonable shape for the maintenance patching 
curve could be represented by a logit function which fit the curve as it 
exists between ages three and ten. The logit function assumes the fol- 
lowing form: 

f(x),/, , f(x)x 
y = e v V(l + e ) 

For each curve group and category, the predicted dependent value 

(MH, Costs) was scaled to equal 0.5 at the tenth year. This occurs 

when f(x) becomes zero and provides a mechanism for establishing the 

desired function of x which was defined as follows: 

f(x) = (Age - 10)/D 

22 



The desired shape of the curve was determined through a trial and error 

process for D for each group and category. Further, the logit function 

f(x) 
was multiplied by 1/e v ' and converted to the following form: 

y - (S/(l ♦ e-< A 9 e - 10 ' /U )) 
The "S" is a scale factor and becomes two times the original model value 
for age 10. The resulting equations for bituminous, concrete and 
combined pavements for both materials dollars and man-hours are shown 
in Table 4. The plotted curves for the material models for the con- 
crete and bituminous sections are illustrated in Figures 4 and 5. 

The model for the maintenance module required for this study must 
predict the quantity of patching required for a given pavement design. 
Therefore, the logit models illustrated in Figure 2 for the concrete 
material and bituminous material were modified to predict quantity as 
follows. For concrete, it was determined that in 1965 (the year in 
which the data was developed) the cost per square yard of pavement for 
concrete was $4.00. Therefore, (136/4) produces 34 square yards of 
concrete per lane mile as the ultimate workload for an infinite age 
concrete pavement. For the bituminous pavements, it was determined 
that in 1965 the cost per ton of bituminous material was $5.00. Assum- 
ing a patching thickness of 2 inches and a unit weight of 140 pounds 
per cubic foot for bituminous materials, then one square yard two 
inches thick equals lh cubic feet of bituminous material or 210 pounds 
per square yard. This results in approximately one-tenth of a ton per 
square yard or 50<£ per square yard. The material cost figure of 552 
then becomes 1100 square yards. Therefore, the models for concrete 

23 



TABLE 4. Logit Models for Pavement Patching 



Models 

Bituminous Pavements 

Material dollars/LM = 552 x (1/ 
Man-hours/LM = 176 x (1/ 

Concrete Pavements 

Material dollars/LM = 136 x (1/ 
Man-hours/LM = 102 x (1/ 

All Pavements 

Material dollars/LM = 142 x (1/ 
Man-hours/LM = 104 x (1/ 



! + g-CAge-lOj/UlSjj 
l + e -(Age-10)/1.20 )) 



l + g-CAge-lO/l.ZSjj 
x + ^(Age-lOl.egjj 



! + g-CAge-lOJl.Sljj 
i + e -(Age-I0)1.51 )) 



24 



600 



LU 



UJ 



< 



o 



O 
O 



< 

LU 



400 




200 



AGE -YEARS 

Figure 4. Patching curves for bituminous concrete pavements. 



25 



150 



UJ 



UJ 



< 

-J 
-J 
O 

o 

I 

I- 
co 
o 
o 



UJ 



100 



50 












10 

AGE -YEARS 



15 



20 



Figure 5. Patching curves for portland cement concrete 
pavements 



26 



and bituminous pavements were as follows: 

c V 4. o/i/ai x -(Age-10)/1.25x 
SY concrete = 34/(1 + e v 3 " ) 

SY bituminous = 1100/(1 + e -(Age-10)/1.16j 

Blowups 

A number of studies have been conducted to identify the cause of 
concrete blowups. v " ; Some of these studies cover pavement histories 
dating back into the Twenties. A number of patterns have been identified 
but no quantitative mechanism has been developed for predicting blowups. 
The concensus is that blowups occur at joints in portland cement con- 
crete pavement when high temperatures and the presence of moisture 
creates excessive expansion of the pavement. These conditions are asso- 
ciated with the summer months and particularly with late afternoons 
following periods of rain. The study results are vague on other causa- 
tions. There is mixed opinion relating blowup frequency to both joint 
spacing and to the presence of expansion joints. There is general agree- 
ment that incompressibles are undesirable in the joint. The incompress- 
ibles reduce the cross-sectional area in the joint to resist expansion 
stresses. Further, incompressibles contribute to joint deterioration 
and spall ing which further weakens the joint section thereby enhancing 
blowups. The consensus is that soft aggregates contribute to blowup fre- 
quency principally because soft aggregates are associated with weak 
Portland cement concrete. 

In all of the studies reviewed, there was agreement that blowup 
frequency increases with pavement age. Examples of this are shown in 
Figure 6 for blowup histories in Michigan and Iowa. The average 

27 



a: 

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0.8- 



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CO 
Q. 

3 



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ffi 



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10 



20 
AGE (YEARS) 



30 



Figure 6. Example of blowup histories in Michigan 

and Iowa compared with model selected for program 



28 



blowup frequency as reported in various state studies was converted to 
blowups per lane mile and summarized in Table 5. Based on this informa- 
tion and the age relationship, the following blowup model was created 
to predict blowups for portland cement concrete pavement: 

Given 

A = Age 

B = Blowup per lane mile/year 

B = 0, A "4 

B = .005(Age - 4), A 7 25 

B = 0, A > 25 
The permanent repair of a blowup is assumed to be included in the 
concrete patching. The additional workload to be associated with the 
blowup will be that of a temporary patch. The reason for this approach 
is that the blowup which occurs in the late afternoon has a major impact 
on traffic and the maintenance crews tend to minimize the extent of the 
repair at that time before making a quality repair when traffic volumes 
are not in their peak. Figure 7 illustrates the tendency of blowups 
to occur in the late afternoon. The blowup is assumed to occur in the 
lanes that are closed in the analysis. 

Mudjacking 

Mud jacking or slabjacking is an activity used by many highway agen- 
cies to correct the settlement or horizontal alignment of rigid pavements 
For one reason or another, voids develop under a rigid pavement. The 
jacking technique involves forcing a slurry or grout mixture under the 



29 



Table 5 . Blowups as reported in 
various studies (28-33) 



Location 



Average Bl 
Lane Mile 


owups per 
Per Year 


Reference 


.05 








28 


.01 








28 


.03 








28 


.10 








28 


.10 








28 


.03 








28 


.05 








29 


.03 








30 


.11 








31 


.12 








32 


.02 








33 



Maryl and 

Ohio Turnpike 

Illinois 

Chicago Expressway 

Iowa 

Wisconsin 

Michigan 

Illinois 

Arkansas 

Connecticut Turnpike 

Indiana 



30 




6 AM 



NOON 



HOUR OF OCCURRENCE . 



Figure 7. Example of documented hours of blowup occurrence 
based on Illinois study (30) 



31 



slab to fill voids. The hydrostatic pressure developed during the 
process also can be used to lift the slab to its proper position. 

There is wide variation in the use of mudjacking by highway agen- 
cies so that it is an activity which may or may not be applicable in 
the model. Even when this technique is used by an agency, its use is 
not necessarily common to all pavements. Holbrook reported that in 
Michigan when mudjacking is practiced, only 22 percent of the rigid 
pavement construction projects had any mudjacking after 15 years of 
service. ' Of these, 11 percent had less than one percent of the 

pavement surface mudjacked. Figure 8 is a graphic presentation of 

(29) 
mudjacking taken from the Oehler and Holbrook report. ' 

Mudjacking when needed occurs early in the life of a rigid pave- 
ment. This is documented by the mudjacking expenditure history experien- 
ced by the Ohio Turnpike. In Table 6, the total expenditures for 
mudjacking on the 241 miles, 4-lane divided tollroad are shown by year. 
Based on a labor wage index, the total expenditures were converted to 
1967 dollars and plotted. A study of the plot suggests a gamma curve 
with mean expenditures occurring in the seventh year. The gamma distri- 
bution for any k = 1, 2, 3, 

fx (x) = xUx^-V** > Q 

K (k-i): x - u 

X is gamma distributed with parameters k and \. The mean value (m ) of 

2 

the function is defined as k/x and the variance (a ) is defined by 

A 

2 
k/x . By assuming a mean of 7 years and a standard deviation of 4 years, 

k and x can be computed by substitution where: 

32 



00 



90- 



80-: 



70-. : 



V) 

t- 
o 
UJ 

o 

Q_ 



60-? 



50-; 



40-. 



LJ 
O 

111 

Q. 



30-. 



20-i 



10-: 



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2.0 



3.0 



— i — 
4.0 



5.0 



6.0 



MUDJACKED AREA , PERCENT PER PROJECT 

Figure 8. History of mudjacking as recorded in a 
Michigan Study by Oehler and Hoi brook (29) 



33 



Table 6. Annual mudjacking expenditures on the 
Ohio Turnpike adjusted to 1967 dollars.* 



YEAR 



LABOR 
RATE 


LABOR INDEX 
(1967) 


REPORTED 
EXPENDITURE 


ADJUSTED 
EXPENDITURE 
(1967) 


1.64 


1.86 


13,173.91 


24,503.47 


1.78 


1.71 


15,579.73 


'26,641.34 


1.85 


1.65 


35,890.68 


59,219.62 


2.02 


1.51 


46,617.48 


70,392.39 


2.13 


1.43 


46,617.89 


66,663.58 


2.31 


1.32 


26,085.89 


34,433.37 


2.45 


1.24 


46,282.92 


57,390.82 


2.54 


1.20 


41,293.45 


49,552.14 


2.60 


1.17 


39,146.91 


45,801.88 


2.65 


1.15 


54,515.89 


62,693.27 


2.88 


1.06 


50,862.79 


53,914.56 


3.05 


1.00 


' 33,167.58 


33,167.58 


3.45 


0.88 


28,940.39 


25,467.54 


3.66 


0.83 


15,766.59 


12,086.27 


3.87 


0.79 


11,101.03 


8,769.81 


4.12 


0.74 


5,607.97 


4,149.90' 


4.23 


0.72 


2,424.17 


1,745:40 


4.58 


0.67 


5,575.30 


3,735.45 



1956 
1957 
1958 
1959 
1960 
1961 
1962 
1963 
1964 
1965 
1966 
1967 
1968 
1969 
1970 
1971 
1972 
1973 



*Total annual expenditures are for labor and material. Material costs 
were minor. Therefore, the adjustment was based on labor alone. 



34 



m x =7 = k/x 

x Y 2 = 16 = k/x 2 

k = 7X 

x 2 = 7^/x 2 = 7/x = 16 

A 

X = 7/16 = .4375 

k = 7 x .4375 = 3.06 
We wish to have an integer number for k so it was made 3. Further, we 
wanted to accelerate mudjacking to create a function which would predict 
100% mudjacking within a 20-year design period. Therefore, a value of 
.5 was assigned to X. This produced the following mudjacking model: 

Y = Annual percent of design life mudjacking 

A 

x = Age in years 

Y Y = .25(.5x) 2 e~' 5x 
This function is plotted in Figure 9 where it has been factored by 
518.52 so it can be compared with the corresponding Ohio Turnpike values, 
The function sums to .9975 for 20 years. 

x=20 2 - 5x 
E .25(.5x) e - ox = .9975 

x=l 

Based on available information, it was assumed that one percent of 
the pavement area will be mud jacked over the life of the pavement, if 
mudjacking is applicable. Therefore, 52.8 feet of each lane mile of 
pavement will be subject to mudjacking. The mudjacking locations will 
be based on slab length. Therefore, for 30-foot joint spacing, there 
will be (52.8/30) = 1.76 mudjack locations per lane mile over the life 



35 



70 



0> 



3 60 - 



CO 

a: 

< 



o 



CO 

Q 

Z 
< 
CO 

Z> 

o 

X 



CO 

< 

UJ 

< 



o 

CD 

< 
-J 



50 



40 



2 - 5X| 
Y= 518.52 I.25C.5X) e "'"" 



^ 30 - 



P 

CO 

o 
o 



20 




AGE (YEARS) 

Figure 9. Curve fit to mudjacking expenditures 
as reported by the Ohio Turnpike after 
conversion to 1967 dollars 



36 



of a rigid pavement. This is the design life mudjacking. The gamma 
model is used annually to determine the percentage of the design life 
mudjacking which occurs each year. 

Joint Sealing 

Concrete contraction joint sealing practices vary widely. Some 
agencies seal concrete joints annually using bituminous sealants. Other 
agencies reduce the frequency through the use of more expensive mater- 
ials including rubberized asphalts and neoprene. The objective in 
contraction joint sealing is to prevent surface moisture from flowing 
into the base and subbase where it can lead to pumping, frost heaving 
and reduced pavement support. 

The contraction joint sealing activity workload will be based 
almost entirely on policy as it relates to sealant material and sealing 
frequency. The material costs will be reflected in the activity stand- 
ard. Therefore, the contraction joint sealing workload can be specified 
entirely through the maintenance level which is defined in Appendix D. 
The workload will be in linear feet of joint sealing and is computed as 
follows: 

W = Annual Workload per lane mile in linear feet 

L = Lane width in feet 

ML = Maintenance level 

S = Joint spacing in feet 

W = ((5280 x L)/S) x ML 



37 



Crack Sealing 

The literature and workload data from recent maintenance manage- 
ment studies revealed that the range of crack sealing varied from 1 to 
10 gallons and from 50 to 100 pounds of filler material per lane mile. 
Some agencies do not seal bituminous cracks contending that it does 
not do any good. Nevertheless, a workload model was developed for 
bituminous crack sealing. It is based on the patching model and an 
average reported quantity. 

First, the reported gallons and pounds of sealant material were 
converted to cubic inches. This was accomplished by assuming the sealant 
to have a specific gravity of one. Conversion of the reported workload 
range to cubic inches is shown in Table 7 producing a range from 231 
to 2770 cubic inches per lane mile. 

Table 7. Joint sealinq material conversion 



Material 


Range 


Conversion 




Pounds 


Gallons 


Factor 


Cubic Inches 


50 


1728/62.4 


1385 


100 




1728/62.4 


2769 




1 


231 


231 




10 


231 


2310 



The workload is expressed in linear feet of cracks to be filled so 
the assumption was made that 10 cubic inches of sealant was needed per 
linear foot of crack. The range of linear feet varies from 23 to 277 
per lane mile from the following computation: 
231/10 = 23.1 
2770/10 = 277 

38 



The average linear feet of crack sealing would be as follows: 

Av. crack sealing per lane mile = (23 + 277 ) = 150 

2 

Assuming that the bituminous pavement is resurfaced after 12 years means 
that the average crack sealing level occurs in the eighth year. To 
modify the bituminous patch model for crack sealing, the coefficient 
must be changed. This is easily accomplished by having the model pre- 
dict 150 linear feet in the eighth year. Substitution of an age of 
eight into the bituminous model results in the prediction of 165 square 
yards of bituminous patching. A direct ratio as follows converts the 
coefficient for crack sealing: 

SY Bituminous Patch = 1100/(1 + e -( A 9 e -10)/l-l e ) 

= 1100/(1 + e" (8 " i )/ 1 - 16 ) = 165 
(150/165) x 1100 = 999.9 

LnFt Crack Sealing = 1000/(1 + e ~( A 9e-10)/l .16^ 

Bituminous Base and Surface Repair 

Information available from the NCHRP 14-1 study and other recent 

(34-37) 
management studies v ' conducted by the consultant and others was 

studied and a range of from .1 to 3 tons of repair per lane mile was 
established as the workload range. The assumption was made that the 
base and surface repair workload would follow the shape of the patching 
model for bituminous pavements. It then became necessary to relate the 
relative level to the patching level. 

An average workload of 1.55 tons of repair per lane mile was con- 
verted to .775 cubic yards by assuming 2 tons of base and surface repair 
equaled one cubic yard. 

39 



The average patching workload for bituminous pavement will occur 
in about the eighth year assuming that the resurfacing occurs in the 
11th or 12th year, so from the patching model the workload in the eighth 
year would be about 165 SY per mile as shown under joint sealing. 

The coefficient for a base and surface repair model can be estab- 
lished by proportioning the .775 cubic yards to the 165 SYs of patch- 
ing in the average year. 

The patching model factor is 1100, so the required base and surface 
repair coefficient becomes (1100 x .775/165) = 5.16. This was rounded 
to 5. Therefore, the base and surface model become 
Cubic Yards = 5/(1 + e^Age-lOj/LlSj 

Composite or Overlayed Concrete Pavement 

The models used for the composite pavement were the same as those 
used in the concrete except that full and partial depth concrete patches 
were replaced by the bituminous patch model and the joint sealing was 
replaced by the crack sealing model. 

Workload Program Modifications 
The workload models outlined for inclusion in the program EAROMAR 
are actually program default workloads. The program is structured to 
permit the user to specify his own workload rates. This can be done in 
two ways. First, the user can directly factor the values generated by 
the default models. In this way, the annual workload rate can be 
increased or decreased to accommodate local conditions. This approach 
retains the influence that the variable age has in the default models. 
The second option available to the user is the specification of a fixed 

40 



r 



annual workload rate. Thus option causes the default model to be by- 
passed completely. This option also can be used to specify workloads 
for activities undefined in the program. 



41 



Axle Loading Modification to Maintenance Workload Models 

It was recognized that maintenance workload models which completely 
ignore the detrimental effect of heavy axle loadings in deteriorating 
the pavement are not completely realistic. However, for those sections 
in the NCHRP Study 14-1 on which the models were based,, the traffic 
volumes, particularly commercial, were not extremely severe. Conse- 
quently, axle loadings did not become a significant variable in the 
workload models. 

Starting in 1967 the consultant developed a series of pavement ser- 
viceability measures en the Illinois Toll Road v " ' The traffic vol- 
ume on this facility is comparable to that which was experienced on the 
sections monitored in the 14-1 study. For the Illinois Toll Road, accu- 
mulated 18-kip axle loadings were computed for each of some 46 differ- 
ent segments of the Toll Road system. The measured serviceability was 
compared with the PSI predicted by the AASHO road test equations and 
revealed that only a portion of the loss in service life could be attri- 
buted to the history of axles to which the pavement had been .subjected. 
This portion ranged from 25 to 50 percent, averaging about 40%. 

The service life measurements, in terms of PSI, were available for 
the Toll Road for its initial year and established by the consultant in 
1967, 1969 and 1971. Drawing a smooth service life curve through these 
four points revealed that almost every section on the Toll Road will 
reach a terminal 1.5 Present Serviceability Index level at an age be- 
tween 19 and 21 years. Figure 10 illustrates four typical curves from 
the Illinois Toll Road Study. The variation in the initial service- 
ability index on the pavement ranged from 3.6 to 4.3. Based on AASHO, 

42 



X 

UJ 
Q 






00 

< 
UJ 

o 

> 

OC 
UJ 
CO 



UJ 
CO 

UJ 

a: 
o. 






5.0 




AGE 

Figure 10. Typical performance curves for sections of the 
Illinois Toll Road where the failure age based on AASHO 
computation would have been 61, 58, 75 and 114 years. 



43 



the axle loading history would have predicted life spans ranging from 

(41) 
41 to 114 years. ' These figures are tabulated in Table 8. There- 
fore, it was concluded that the deterioration of the Illinois Toll Road 
riding surface proved to be almost completely independent of axle load- 
ings and the initial Present Serviceability Index. In another study 
by Utah, it also was shown that loss of PSI was more related to age than 
18-kip axle loads. ' These results suggest that the pavement model 
developed from the NCHRP 14-1 data, where the maintenance requirements 
are strictly a function of age, is an appropriate model for roads with 
this level of traffic. 

In a comparable study conducted in the Chicago area on the express- 
way system, the measured present serviceability values closely followed 

(42-44) 
the AASHO road test predictions/ ' In this case, the measure of 

serviceability could be almost entirely attributed to axle loadings. 

So, although the maintenance workload models are acceptable for normal 
traffic loading levels, there will be times when a pavement^will be sub- 
jected to an extremely large accumulation of axle loadings. When this 
happens, the workload models must be modified to accommodate the pronoun- 
ced axle loading effects. 

For purposes of the program analysis, a definition was needed for 
normal traffic. The definition established is based on the AASHO road 
test equations which predict the accumulated 18-kip axle loads to 
pavement failure (1.5 PSI). 

The two failure equations from the AASHO road test study used in 
the analysis program follow: 

44 



Table 8 . Pavement serviceability relationships based on 
Illinois Toll Roads studies 



Base Year 


Annual Increase 












Act 


ual 


Predict 


ion 


Base Year 


18 -Kip Axle 


in 18 -Kip Axle 


AASH0 


Based 


Years 


of 


Fai 


lure Based 


Present 


Loadings in 


Loadings in 


to 


Fa 


ilure 


for 


10- 


on 


Se 


rvice-Li 


fe 


Serviceabil ity 


Millions 


Millions 


in 


ch 


PCC Pavement 




H 


i story 




Index 


2.19 


.02 






75 










19 




3.90 


2.33 


.12 






45 










21 




3.60 


.88 


.22 






41 










20 




3.60 


.73 


.22 






42 










20 




3.95 


.88 


.19 






44 










19 




3.85 


1.90 


.17 






41 










20 




4.00 


1.02 


.11 






55 










20 




4.00 


.95 


.04 






84 










19 




4.30 


1.24 


.14 






48 










19 




4.20 


1.02 


.16 






47 










19 




4.00 


.73 


.12 






55 










19 




3.95 


.58 


.10 






61 










19 




3.95 


.22 


.03 






114 










20 






1.09 


.19 






43 










20 




4.05 


.88 


.20 






43 










19 




4.05 


.73 


.22 






42 










20 




3.80 


.44 


.13 






55 










21 




3.70 


.37 


.11 






58 










20 




4.25 


.22 


.12 






65 










20 




4.05 


.37 


.09 






66 










20 




4.05 


.15 


.12 






60 










20 




3.50 


.95 


.04 






84 










21 




3.85 



45 



Concrete Pavement Equation 

T = Pavement thickness inches 

p = Accumulated 18-kip equivalent axle loadings to produce 
a terminal PSI value of 1.5 

P = (10 5 ' 85 (T+l) 7 ' 35 )/(19 4 - 62) 
Bituminous pavement equation 

D = Equivalent pavement thickness 

D 1 = Surface thickness inches 

D 2 = Base thickness inches 

D_ = Subbase thickness inches 

D = ,43D 1 + .14D 2 + .11D 3 

p = Accumulated 18-kip equivalent axle loadings to produce 
a terminal PSI value of 1.5 

p = (10 5 ' 93 (D+1) 9 ' 36 /(19 4 - 33 ) 
An initial step in the program analysis process is the computation of the 
18-kip accumulated axle loads required to fail a designed pavement based 
on the above AASHO equations. 

Normal traffic is defined as any accumulated 18-axle loadings that do 
not exceed the accumulated axles computed by assuming a uniform annual 
loading rate which will produce the AASHO failure loading in twenty years. 
For example, the substitution of a 10-inch PCC pavement design into the 
AASHO equation predicts that the following axle loadings are required 
to produce pavement failure: 

P = 10 5 ' 85 (10 + l) 7 - 35 )/(19 4 ' 62 ) 

p = 39.48 x 10 6 

46 



Therefore, the limiting annual axle loading rate for normal traffic 
becomes 

39.48 x 10 6 /20 = 1.97 x 10 6 18-kip axles/yr. 
In the analysis, the program generates 18-kip axle loadings based on 
traffic input parameters. As long as these loadings do not exceed the 
normal levels, no workload model modifications are required. As an 
example, assume that at the end of ten years 18 x 10 - 18-kip axles 
had been accumulated. The normal level at the end of ten years is as 
follows: 

(1.97 x 10 6 ) x (10) = 19.7 x 10 6 
Because 18 x 10 is less than 19.7 x 10 , we are within the normal range 
and therefore no model modification is needed. If, however, the analysis 
had produced 25 x 10 accumulated axle loadings at the end of ten years, 
a modification would be required. The modification not only applies to 
the workload models but to the pavement rehabilitation logic. 

Under normal traffic loading conditions, the pavement is assumed to 
deteriorate at a uniform rate over time. This uniform deterioration is 
expressed in terms of a uniform loss of psi. In the program, a PSI of 
4.5 is assigned to any new pavement. Failure has been defined as 1.5 PSI, 
Therefore, the normal deterioration process results in a .15 PSI loss per 
year over 20 years. 

(4.5 - 1.5)/20 = .15 
This assumption of a linear loss in PSI serves as the basis for the modi- 
fication to the workload models. 



47 



Under normal traffic loading conditions the PSI loss is linear 
and requires 20 years to reach 1.5 PSI. The age used in the workload 
models is based on this deterioration process over a twenty-year period. 
If the deterioration process is accelerated because of an excessive axle 
loading rate, the pavement will fail prior to the 20th year. However, the 
maintenance workload at failure should be comparable to the workload at 
the 20th year under the normal deterioration process. Therefore, a 
value of twenty should be used for age in the workload model. The "20" 
is defined as an equivalent age based on the accelerated deterioration 
process. The total accumulated 18-kip axles required to fail the pave- 
ment are equated to the total available PSI loss to failure, or 
39.48 x 10 6 18-kip loading = 3.00 PSI 

and annually 

1.98 x 10 6 18-kip loadings = .15 PSI. 
Therefore, for purposes of modifying the pavement patching model, the 
following procedure was established: 

A. If the pavement design module provides a PSI value then 
the program determines an equivalent age based on a linear 
interpolation of a total loss of PSI over 20 years. 

B. If the pavement design module transfer no PSI value but 

an axle loading value (18-kips accumulated loadings for the 
pavements present age), the program compares the transferred 
axles to the normal traffic loadings, which are based on a 
linear interpretation of accumulated loadings to a terminal 
value of 1.5 in 20 years. If the actual loading exceeds the 

48 



normal loading for a given age, then the PSI is set equal 
to a comparable axle loading year. 

C. If the program provides neither a PSI nor an accumulated 
loading value, then the accumulated loading will be based 
on the commercial volume and the commercial axle distribu- 
tion defined for the program. This computed accumulated 
axle loading value is compared with an AASHO predicted axle 
loading value based on a linear interpolation over 20 years. 
Again, if the actual loading (based on volume) exceeds the 
predicted loading required, then the age is increased to a com- 
parable axle loading year. 

The following are examples of the three conditions A, B, and C as 
handled by the program: 

A. Given: PSI = 2.0, Age = 10 years 

With an initial PSI of 4.5, the PSI value at age ten would 
normally be the following: 

4.5 - (10 x .15) = 3.0 
However, the PSI is given, so an equivalent age is determined. 
This is computed as follows: 

Age = 20 x (4.5 - 2.0)/3 = 16.67 years 

B. Given: 18-kip Accumulated Loading = 23 x 10 6 

Age = 10 years 
Concrete thickness = 10 inches 



49 



From the concrete equation on Page 46 the accumulated 

18-kip loadings to failure (PSI = 1.5) is 39.48 x 10 6 . 

This would produce 19.74 x 10 in ten years. The actual 

loading exceeds this value so the equivalent age is de- 
termined as follows: 

c — 

Age = 23 x 10 x 20 = 11.64 years 

39.48 x 10 6 

The program uses an age of 11.64 in the maintenance work- 
load models. Further, the psi is based on the equivalent 
age in a linear interpolation over 20 years. 

C. The modification here is the same as in B. The only differ- 
ence is that program generates an accumulated axle loading 
for each analysis year. 

A schematic of options A, B, and C is illustrated in Figure 11. 

The 18-kip equivalent axle loading factor used in the program is 
based on the vehicle distribution shown in Table 9 where the composite 
18-kip axles are shown to be 735 per 1000 commercial vehicles. 



50 





Pavement 
Systems 




Costs 




Design 












Option A (PSI) 










i 


— i 


rn dama D 






hAKUMAK 






AGE=F(PSI) 




Option B (AXLES) 














i 


=1 cz 


1 










i 










EAROMAR 






PSI=F(AXLE) 
AGE=F(PSI) 




; Option C 
























i 




rn nOMA D 




J 


hAKUMAK 






AXLE=F(V0L) 
PSI=F(AXLE) 
AGE=F(PSI) 




'■^rV: ' -■ 










.?" T" 




1 






'.-'■ 


i 


b LZ 


1 





Figure 11. Schematic of PSI axle loading and null transfer 
options available to pavement systems design program in 
accessing program EAROMAR, Economic Analysis of Roadway 
Occupancy for Maintenance and Reconstruction 



51 



Table 9 . Equivalent 18-kip single axle 
loads per thousand vehicles. 



18-K equivalents per 1000 Vehicles 















Commercial 


Vehicle Description 




Observed 


Overloaded 


Combin 


ed 


Percentage 


4 tire 




0.4 


— 







— 


2 axle 6 tire 




134 


3360 


247 




27 


3 axle single 




422 


2160 


482 




6 


3 axle combination 




448 


6720 


667 




12 


4 axle combination 




752 


5520 


919 




26 


5 or more axle combin 


ation 


990 


4320 


1106 




29 



Weighted Average 735 100 



Source: "Illinois State Toll Highway System. . .Long Range Pavement Maintenance 
Program." Bertram D. Tallamy Associates for the Illinois State 
Toll Highway Commission, March 1968. 



52 



W.ork Requirements 

Once the workload is established or accumulated through a given 
analysis year through the use of the workload models, it becomes 
necessary to convert this into maintenance costs and motorist impacts. 
This requires a determination of the hours needed for work crews to 
perform the predicted annual workload for each work activity. 

For a fixed workload, these hours can vary widely, depending on 
local policy and practices. Some of the influences are as follows. 

1. The total available worktime for each crew 

2. The policy decisions relating to the periods when the 

road can be occupied 

3. The cure time available for performing the work as the 

crew must terminate productive activity within the 
production and cure time 

4. Lunch hour policies relating to occupancy 

5. The travel allowance for the crew to move from the crew 

quarters or garage facilities to the work site on the 
roadway and return 

6. The time required for the installation of traffic control 

7. The time spent moving between worksites within a traffic 

control zone and between traffic control zones 

8. The length and character of the work zone 

9. The productivity of the work crew 

10. The level of maintenance which controls how frequently 
road will be occupied to perform work 

53 



Each of the above factors is part of a simulation process de- 
veloped to determine the crew hours and the hours of roadway occupancy 
needed to perform the activity workload which is generated by the 
workload models. 

The program, which was designed to perform the economic analysis, 
permits each of the above factors to be specified by the program user. 

Simulation Process 

The expected wide variations relating to constraints on the 
performance of work dictated a simulation of the work as a reasonable 
approach to the development of work time requirements. In general, 
the simulation process involves the following steps anytime an annual 
workload for an activity has been determined: 

1. The maintenance level for the activity is examined and a 
determination made of the workload to be performed during 
the simulation process. Three options are possible: 

A. No work will be simulated and the workload will be held 
over to be added to the workload generated in the next 
analysis year 

B. All the workload wilT'oe included in the simulation 

C. The workload can be divided into a number of equal parts 
and one part will be simulated 

2. The roadway constraints are examined and the first hour of 
occupancy determined. 

3. The magnitude and location of the first worksite is computed. 

54 



4. The crew is assigned to the first worksite and based on pro- 
duction data, the time required to complete the work computed. 

5. The elapsed time available for roadway occupancy is computed 
and is based on crew and occupancy constraints. 

6. The time required to move to and complete work at the next 
worksite is added to expended work time, and if within the 
available elapsed time, the simulation continues to iterate. 

7. Following the termination of each occupancy interval, crew 
hours and occupancy hours by hour are accumulated. 

8. The simulation process is performed for each feasible lane 
closure for each work activity. 

Worksite 

The wide variation in the way maintenance is handled by different 
state agencies directed the decision to use a roadway occupancy simula- 
tion process to predict the hours of roadway occupancy. One of the 
variables is the magnitude of the work which will be performed at each 
worksite. This variable can be random and the result of local policy 
and practice. 

Pavement patching represents the major activity where random 
variations will occur in worksite size. Therefore, it was decided to 
establish an array of random size patches in the program. Also, work- 
site locations will be randomly spaced and this in conjunction with 
random worksite sizes will produce considerable variations in the re- 
quired roadway occupancy periods, particularly when subjected to local 

55 



constraints relating to permitted occupancy hours and work crew 
schedules. 

Three random arrays are established in the program. These are 
full depth concrete patching, partial depth concrete patching and a 
roadway location random number. Each array numbers 1000 and this 
represents the maximum number of iterations permitted in the roadway 
occupancy simulation for a given activity. 

The magnitude and the character of the simulation process can be 
input to the program for each activity by the user. In this way, the 
user can structure the work process to resemble local practices. 

The character of the simulation process is controlled by the 
following elements: 

1. Size of worksite 

2. Number of simulation iterations 

3. Spacing of worksite locations 

Size of Worksite 
Use is made of the two random size patch arrays when the worksite 

varies. Further, the size can be modified through the use of a factor 

or an add on permitting wide flexibility in establishing the amount of 

work which will be done at each worksite. 

A third option available to the user in the establishment of work 

at a worksite is the number of lanes closed to traffic. As an example, 

in joint sealing, the linear feet at each worksite would double if two 

lanes instead of one lane were closed to traffic. 

56 



The computation of the magnitude of the worksite in the program 

is structured in the following manner: 

W. = Worksite type where : 

l\L = Full size patch in square yards 
Wp = Partial depth patch in square feet 
IaL = Lanes closed 

F = Worksite type multiplier 

A = Worksite type add-on 

S = Magnitude of the work at each worksite 

S = W. x F + A •, ,■ 

Simulation Interations 
The user can control the magnitude of the simulation process used 
to establish the required hours of roadway occupancy. This is necessary 
because there may be no need to simulate an occupancy process when there 
is no variation in the work process. As an example, a concrete blowup 
requires that crews occupy the road at one worksite, perform work and 
leave the roadway. If the workload is specified as sites, then repeated 
iterations would be redundant. In, this case a single iteration of the 
simulation would produce the same results and therefore is all that 
should be specified to the program. 

Spacing 
Two options are available in the specification of worksite spacing. 

These are random and uniform. The array holding the roadway location 
random numbers is arranged in ascending order. When the random option 
is specified, this array is used to sequentially establish the location 

57 



of worksites. The simulation process is independent of activity work- 
load with the exception of the establishment of random worksite locations, 

The annual workload is used to determine the total mileage over 
which the simulation process will take place. This is done in the follow- 
ing way : 

A = Annual workload per lane mile 

SW = Simulation workload 

L = Lanes closed 

R = Random number between and 1 

Sta.= Worksite location mileage station 

Sta.= (SW/(A x L)) x R 
Where the annual workload is small relative to the simulation work- 
load, worksites will be very far apart. As workload increases, the 
distance decreases because the simulation workload is constant. Also, 
if multiple lanes are closed then the worksites become closer together 
because the random site could be in any lane. 

The other spacing option is uniform. In this case, a variable 
which describes the spacing between worksites is used to establish 
each worksite location. Typically, concrete joint sealing might be 
performed at every joint, once every three years. The spacing desired 
in this case would be the distance between joints. 

Full Depth Concrete Patch Distribution 
Based on a range of studies made by the consultant, the assumption 

58 



was made that the full depth concrete patches required for a portland 
cement concrete pavement range from 3 1 x 12' to 60' x 12' . It was 
determined that a good frequency distribution to reflect the size of 
full depth concrete patches is the gamma distribution. In this 
function, G(k,A), k is a shape parameter and A can be interpreted as 
a scaling parameter. The gamma distribution is for any k = 1, 2, 3, .. 
fs k (x) - A(xx)^e-" , where x ; Q 

X is gamma distributed with parameters k and A. For the concrete patch 
size distribution it was assumed that the mean patch size would be 
12' x 12'. The standard deviation for the patch was assumed to be 
4' x 12'. Assuming a constant 12-foot width, the mean length of the 
patch is 12 feet and the standard deviation is 4 feet. By integration 
or, more simply, by consideration of x as the sum of k independent 
exponentially distributed random variables, if x is G(k,A), then 



and 



m 

X 


= k/A 




2 

ax 


2 
= k/A 




or 


the k and A 


value 


m 

X 


= 12 




2 

a x 


= 16 




k 


= 12A 




16 


= 12A/A 2 = 


= 12/A 



\ = 12/16 = .75 

59 



N 



k = 12 x .75 = 9 
Therefore, where x is the length of the 12-foot wide patch, the 
density function for the distribution of full depth concrete patches 
becomes: 

F(x) = .75(.75x) 8 (e"' 75x ) 
40320 

A graphic plot of this distribution is illustrated in Figure 12 where 

a factor value of 9.6 has been applied to create an F (x) range from 

to 1. 

Partial Depth Concrete Distribution 
Based on studies conducted by the consultant, it was possible to 
develop a frequency distribution for the size of partial depth concrete 
pavement patches. A frequency distribution was plotted and again it 
seemed that a gamma distribution would be an appropriate shape to des- 
cribe the distribution of partial depth concrete patch sizes. From the 
plot, it was determined to make the mean patch size three square feet 
and the standard deviation two square feet. We can solve for the k and 
A values by substitution where: 

m = 3 = k/A 

x ' 



2 

a 
X 


= 


4 = 


2 

k/A 




k 


= 


3A 






2 

a 
X 


= 


2 
3A/X 


= 3/A 




A 


= 


3/4 






k 


= 


3(3/4) 


= 9/4 


60 



1.0 



F(X) = 



(.75»x) 8 e" (75x) 

5600 




35 



Figure 12. Frequency distribution developed for full 
depth concrete patching 



61 



Therefore, where x is the area of a partial depth concrete patch, the 
density function becomes 

F(x) = .75(.75x) 1,5 e"- 75x x Factor 
(1.5)! 

This function could not be expanded, but through a trial and error pro- 
cess, the following function was established to fit the frequency dis- 
tribution shown in Figure 13. 

F(x) = 2.2(.75x) 1 - 5 e"' 75x + .1 



62 






F Y (X) = 2.2 (.75 X) e 




1.5 -1.75X) 



* .1 



15 20 25 30 

PATCH SIZEISQ. FT.) 



35 



40 



Figure 13. Frequency distribution developed for partial 
depth concrete patching 



63 



Performance Standards 

Based on the TRB-AASHTO Joint Study of Maintenance and Operations 

(46) 
Personnel v y , 44 of the 50 states have or contemplate having a 

maintenance management system or maintenance performance budget method 

of operations. Both of these systems make use of maintenance work 

activity performance standards which describe the procedures to be 

followed, the men, equipment and materials to be used, and the rate 

of production to be achieved. 

Because of the wide use made of performance standards by the states, 
it was decided to structure the program developed for the Economic Ana- 
lysis of roadway occupancy for maintenance and rehabilitation in such 
a way that each state could readily use their own performance standard 
data in the development of maintenance and rehabilitation costs. 

A typical performance standard is illustrated in Figure 14. This 
crack filling standard shows that a five-man crew using 2 dump trucks, 
1 heating kettle, and a compressor, can place 500 pounds of crack sealer 
per hour. This particular standard reflects the production rate which 
is achieved on the roadway. If a state has structured its performance 
standard production rate to include travel to the job site, it should 
be adjusted to accommodate the crew travel time specified in the program. 

In the program, occupancy time is determined by simulating the per- 
formance of a crew. This simulation includes the following elements: 

1. Travel time to and from the roadway 

2. Time for the installation and removal of traffic control 
signing and delineation 

64 



State of Nevada 
Department of Highways 
Maintenance Division 



MAINTENANCE PERFORMANCE STANDARDS 



ACTIVITY NO. 



101.07 



ACTIVITY 



Crack Filling 



ACCOMPLISHMENT UNIT 



Pounds Filler Material 



ACTIVITY REQUIREMENTS 



MEN 



EQUIPMENT 



MATERIALS 



NO. 



CLASS 



NO. 



TYPE 



AMOUNT 



DESCRIPTION 



Maintainers 



Dump Trucks Single 1 lb. 

Axle 
Asphalt Kettle 

(Heating) 
Compressor with nozz]| 

to clean cracks 



Crack Filler (Pounds) 



PRODUCTIVITY DATA 



Unit/Crew Hr. 

500// Filler/Crew Hr. 



Unit/Man Hr. 

100// Filler/Man Hr. 



Crew Hr. / Unit 

0.002 Crew Hr///Filler 



Man Hr./Unit 

0.010 Man Hr///Filler 



QUALITY GUIDE 



Condition: Asphalt surfacing cracked to a point to admit penetration of water. 
Fill cracks when they exceed 1/4" in width. 



Maintenance Level : Fill cracks and joints to level of travelled surface. Work 
should be done in fall. 



Frequency or Workload Rate: 

140 pounds of filler per mile of 24' bituminous surface. 



Figure 14. Typical maintenance performance standard 



65 



3. Production work at a single work site 

4. Move time between work sites 

5. Material cure time on the roadway 

The production rate used in the program should reflect the production 
which can be achieved at the work site. 

The performance standard for full depth concrete patching being 
used as the default in the program is summarized as follows. It is 
based on standard time data and the resulting performance standard 
which was developed in conjunction with NCHRP Study 14-2 presently 
being reviewed by the Transportation Research Board. 
Activity: Full Depth PCC Patching 

Crew Equipment Materials 

1 Concrete Saw Ready-mix PCC 
1 Foreman 1 Water Truck 

3 Equipment Operators 1 Hydraulic Ram 
3 Laborers 1 Front End Loader 

3 Dump Trucks 

Production Rate - 75 cubic feet per hour. 
This information must be converted to fit the program format where the 
following elements are needed: 

1. Crew hourly costs 

2. Material costs per workload unit 

3. Production rate in workload units per hour 

The workload model in the program predicts square yards of full depth 
Portland cement concrete patching. Therefore, both the material and 



66 



production rate must be converted to reflect accomplishment units of 
square yards. Hourly unit costs must be applied to crew members and 
equipment and the accomplishment units costed for material. 

Table 10 shows average hourly wage rates * ', typical equipment 

(37) (37) 

rental schedule v ', and typical material unit costs v ' . Unit costs 

from this table have been used in the example shown below to illustrate 

how the performance standard data is converted to fit the program format, 

Activity: 9" Portland Cement Concrete Full Depth Patching 



Number 


Classification 


Hourly Unit 


Cost 


Hourly Cost 


1 


Foreman 


4.63 






$ 4.63 


2 


Equipment Operator II 


3.60 






7.20 


1 - 


Section Man 


4.29 






4.29 


3 


Laborers 


2.86 






8.58 






Total 


Labor 


$24.70 


1 


Concrete Saw 


1.00 






$ 1.00 


1 


Water Truck 


2.00 






2.00 


1 


Hydraulic Ram 


8.20 






8.20 


1 


Front End Loader 


5.00 






5.00 


2 


Dump Truck 


3.75 






7.50 



Total Equipment $23.70 
Labor and Equipment Costs $48.40/Hr. 

Material 

Ready mix @ 25.00 per cy 
25 x 9/36 = 6.25/SY 



67 



Table 10. Typical hourly labor rates (46) 

equipment rental rates (37), and material 
unit costs (37) 



EQUIPMENT RATES 




LABOR RATES 






Description 


Hourly 


Description 


Monthly 


Hourly 


Mileage Vehicles 


$ .20 


Gang Foreman 


$803 


$4.63 


9,000 GVW Trucks 


1.75 


Section Man 


743 


4.29 


(Garbage & Service) 




Common Laborer 


496 


2.86 


Trucks Dump Single Axle 


3.75 


Skilled Laborer 


652 


3.76 


• Trucks Dump Tandem Axle 


6.50 


Equipment Operator I 


566 


3.27 


Trucks, Tractor 


6.00 


Equipment Operator II 


624 


3.60 


Trucks, All Wheel Drive 


7.25 


Equipment Operator III 


711 


4.10 


Trucks, Flatrack 


3.85 








Trucks, Service (Sign 










Service, Boom, Lube, 










Drill , Mech.) 


3.50 








Line Stripper 


11.00 








Traction Broom 


4.25 








Street Sweeper (S.P.) 
Street Flusher (Semi-Mount) 


7.00 
2.70 














Compressors 


2.75 








Cranes and Fork Lifts 


.50 








Distributors (Truck or 










Semi -Mounted) 


4.50 








Maintenance Distributors 










(Pot Type to 600 Gal.) 


3.00 








Motor Graders 


5.80 








Pul vimixer 


11.50 


MATERIAL UNIT COST 






Chip Spreader Box and 










Windrow Sizer (Towed) 


2.00 


Description 


Units 


Unit Cost 


Loaders (Except Industrial 










Style Tractors) 


5.00 


Aqgreqate 


CY 


3.14 


Conveyors 


3.50 


Screenings 


CY 


7.28 


Conveyor W/Screens 


8.25 


Bituminous Mix 


CF 


8.64 


Concrete Mixers 


2.80 


Chlorides (Salt) 


TNS 


15.00 


Patcheaters (Towed) 


3.00 


Salt and Sand 


TNS 


5.30 


Mowers, Rockpickers, 




Plantmix 


CY 


9.00 


Roto Shredders, Maintainer 


7.25 


Expansion Joint Filler 






Ram, Hydraulic 


8.20 


Material 


LBS 


.30 


Rotary Plows 


60.00 


Cement 


SACKS 


2.50 


Rollers Pulled 


.85 


Concrete 


CY 


25.00 


Rollers, Steel Wheel 




Liquid Asphalt 


GAL 


.40 


(Includes Vibratory) 


7.85 


Crack and Joint Fil ler 


LB 


.08 


Rollers, Pneumatic Tired 


11.00 


Fertil izer(Pounds) 


LB 


.10 


Shovel and Backhoe Combination, 




Fertilizer (Gallons) 


GAL 


8.50 


Truck Mounted 


9.00 


Insecticides ft Herbicides 




Welders, Trailer Mounted 


2.00 


(Pounds) 


LB 


2.00 


Electric Plants 


2.00 


Propane Cylinders (100 






Water Tanks, Trailer Mounted 


2.00 


Lb) 


LB 


10.00 


Tractors, Industrial 




Propane (Bulk Gallons) 


GAL 


.35 


W/Attachments (Loader, 




Guide Posts 


EA 


2.25 


Auger, etc.) 


3.25 


Sight Plates & 






Tractors, Crawlers 


9.00 


Guardrail Delineators 


EA 


.38 


Snow Tractor W/Dozer 


2.50 


Marker PI ates 


EA 


3.55 


Carryall Scrapers 


2.80 


Snow Poles 


EA 


1.50 


Rippers 


1.00 


Signs 


EA 


3.85 


Saw 


1.00 


White Paint 


GAL 


3.63 


Air Hammer 


.50 


Glass Beads 


LBS 


.13 


Trailers, Cargo or 




Yellow Paint 


GAL 


4.35 


Tilt 


3. on 


Paint Thinner 


GAL 


.70 


Trailers, Dump 


5.25 


Sign Posts 


EA 


.81 


Classrooms 


15.00 


Fence Posts 


EA 


2.50 


Trailers, Utility 


.85 


Fencing 


LF 


.20 


Chip Spreader(S.P.) 


16.00 


Steel Guardrail 


LF 


2.30 


Heater Planer, (Towed) 


15.00 


Steel Cattlequard 


EA 


33.00 


Screening Plants 


5.50 


Culvert Pipe, 18-inch 


LF 


3.65 


Mobile Drill 


9.00 


Culvert Pipe, 24-inch 


LF 


4.75 


Crushing Plant 


15.00 


Culvert Pipe, 30-inch 


LF 


6.90 


Lab Trailers 


.75 


Culvert Pipe, 36-inch 


LF 


8.29 


Line Striper (Small 




Culvert Pipe, 48-inch 


LF 


15.25 


Self-Propel led) 


3.00 


Guardrail Posts 


EA 


18.00 



68 



Production Rate 

75 cubic feet/hour 

75/(9 x 9/12) = 11.1 sq. yd. per hour 

The three values needed to completely describe the activity, PCC 
full depth patching, have now been established. In summary they are: 

1. $48.40 crew hourly costs 

2. $6.25 material work unit costs 

3. 11.1 SY per hour workload production rate 

The activity standards used in the program are shown in Table 11 
and the resulting program default matrix for the activity performance 
data is shown in Table 12. 



69 



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71 



MOTORIST MODULE 

The motorist impacts due to roadway occupancy include operation 
costs, loss time, changes in accident potential and pollution emissions 
To effectively evaluate these impacts requires the development of the 
following information: 

1. The hourly volume of traffic on the roadway by direction 

2. The composition of the hourly volume by trip purpose 

3. The average highway speeds during normal conditions 

4. The average highway speeds, speed changes and delays created 
by a roadway occupancy 

5. The accident potential under normal and restricted operation 

6. Pollution emission rates as a function of average highway 
speed 

7. Vehicle operation costs as a function of speed and vehicle 
weight for freeway alignment 

8. Value of loss time 

9. Accidents and cost under normal and roadway occupancy condi- 
tions 

The development of this required information has been divided into 
speed, traffic, operation cost, value of time, accidents, and pollution, 

Most of the information needed to analyze motorist impacts on a 
given freeway segment will be unique for that segment. This includes 
traffic, roadway occupancy constraints, and the freeway design. 

In the development of a computer program to perform the economic 
analysis of roadway occupancy, it was decided to structure the program 

72 



to accommodate local conditions. This was accomplished by designing 
optional input provisions for the program. However, basic informational 
elements needed to be incorporated directly into the program, therefore, 
all data needed to execute the program was assigned through data state- 
ments. These program default values will be used in the execution of the 
program unless a user elects to input and override the default values. 

The program is designed to perform a complete economic analysis for 
each applicable work activity annually by roadway direction. Further, 
every feasible roadway closure sequence is considered. The number of 
roadway closure options available depends on the freeway lanes. The con- 
figurations considered by the program are illustrated in Figures 15 
through 19. In Figure 15 and 16, the lane closures possible with an 
eight-lane divided roadway are illustrated. These include four lanes 
closed and traffic detoured to two lanes in Figure 15-A, three lanes 
closed in 15-B, two lanes closed in 15-C, one lane closed in 16-A and 
four lanes closed with traffic crossover to two lanes in opposition direc- 
tion in 16-B. The user also can specify the use of either one or two 
shoulders which increases the capacity for each feasible lane closure and 
provides an additional option to traffic when all lanes are closed. 

In the economic analysis of roadway occupancy, different closure 
strategies are examined. A strategy consists of a sequence of lane clo- 
sures which has been designated a closure category for purpose of the eco- 
nomic analysis. The feasible closure categories available for use with 
an eight-lane freeway where shoulder use is not permitted are as follows: 



73 



A. 4 lanes closed, Detour 








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74 



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and crossover on an eight-lane freeway 



75 



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a crossover for a six-lane freeway 



76 



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for a four-lane freeway 



77 





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used for traffic. 



78 



Closure Category No. 1 = Four directional lanes closed and traffic 

diverted to a detour. 

Closure Category No. 2 = Three, then one, directional lane closed. 

Closure Category No. 3 = Two, then two, directional lanes closed. 

Closure Category No. 4 = One directional lane closed at a time. 

Closure Category No. 5 = Four directional lanes closed and traffic 

crossed over to two opposite directional 
lanes. 

When shoulders are specified as being available, the detour option 
is not used; rather, four directional lanes are closed and traffic oper- 
ates on the shoulder. This change in Closure Category No. 1 applies 
for the specification of either one or two shoulders. 

A similar set of closure categories is applicable to the six- and 
four-lane divided highway. In the analysis process all feasible closure 
categories are examined for a given freeway. In support of a pavement 
systems design, only the closure category which produces the minimum 
direct activity and motorist costs for each activity is used in the genera- 
tion of total roadway occupancy costs. 



79 



Speed 

The most critical component of the economic analysis of roadway 
occupancy is the change in operating speed of vehicles on a freeway 
during the occupancy period. 

An extensive field data collection program was designed and 
implemented in an effort to adequately quantify the behavior of 
traffic during roadway occupancy conditions. 

The field data collection procedures were designed to develop 
speed profiles on a wide range of closure conditions for operation 
on 4-, 6-, and 8-lane freeways. The mechanics of the collection 
effort were automated as much as possible to improve the reliability 
of the data developed and to expedite data reduction efforts. 

Instrumentation 
A simple oscillator was built to be attached to a test vehicle's 

speedometer. The oscillator was housed in a small box and was powered 
by the car's battery. The oscillator generated three different fre- 
quency signals, which were monitored using a small, inexpensive portable 
cassette tape recorder. The middle frequency was used to signify that 
a test was in progress on the tape. This middle frequency is illustra- 
ted in Figure 20 as the test frequency. 

A low frequency signal was generated for each rotation of a shaft 
attached to the frequency box. The shaft through an extension was 
attached directly to the speedometer cable using a T connector. This 
speedometer-excited frequency signal v/as a function of the speed 

80 




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81 



.of the vehicle and is illustrated in Figure 21. Finally, the third 
signal was controlled by the vehicle driver and served as an event 
marker. This is illustrated in Figure 22. The circuit diagram for 
the oscillator box is included in Appendix A. 

Field Study 

In developing speed profile data, a test vehicle normally opera- 
ted between interchanges. The test period was approximately 45 min- 
utes, being controlled by the length of the tape recorder cassette 
tape. The test frequency was turned on after the tape recorder was 
running and the speedometer frequency was switched on just prior to 
entering the freeway. Both frequencies were left on for the duration 
of the cassette recorder tape. The test vehicle driver made repeated 
passes through the traffic control zone noting with his event fre- 
quency switch the location of observers stationed at both ends of the 
work zone. This is illustrated in Figure 23. 

The observers were placed at each end of the work zone and also 
were equipped with oscillator boxes and cassette tape recorders. The 
observers' function was to develop traffic counts, vehicle headways 
and lapsed time data for vehicles passing through the work zone. 

The oscillators used by the observers had three switches; a 
middle test frequency, a low frequency for normal events and a high 
frequency for control events. The test frequency, as with the test 
vehicle, was needed to signal the presence of test data on the 
cassette tape. The normal event switch was excited for each passing 

82 




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85 



.vehicle. The control event was used to record the passing of the test 
vehicle which permitted the data collected by the test vehicle and by 
observers to be coordinated. 

Date Reduction 

The field data collection effort produced a series of cassette 
tapes. Each tape represented a time continuum with two types of events. 
The next step was to convert this tape information into a form which 
could be interpreted into speed profiles, lapse times and traffic volume, 

The data from the cassette tapes was consolidated onto tracks of 
a %-inch tape reel. These %-inch reels were processed through an analog 
computer to create a digital readout of times for each frequency event 
on the tapes. This was accomplished as follows: 

1. A program board was designed to identify the three frequency 
signals on the tape. 

2. A time pulser was set to output 1/100 of a second signals 
which were counted by an accumulator and held. 

3. The %-inch tape reel was processed at a constant rate by 
the analog computer and e\/ery frequency signal above or 
below the test signal was identified. 

4. As each signal was sensed, it was assigned the value of the 
accumulated number residing in the pulse hold area. 

5. The numbers for frequency signals above the test frequency 
were made negative to differentiate them from the frequencies 
signals below the test frequencies. 

86 



6. The resulting digital numbers were placed in a file on a 
digital computer tape. 

Once the conversion to digital tapes was complete, it was nec- 
essary to develop computer programs to convert the digital data to 
speed profiles, volumes and lapse time data. A speed was developed 
for e^ery second of lapse time. A typical computer generated table 
of speeds is shown in Table 13. This provided about a 1% accuracy 
for the speed profiles. The volume data was structured to reflect 
hourly volumes at intervals of 1, 2, 3, 4, 5, and 10 minutes. A 
typical volume printout is illustrated in Table 14. The lapse time 
data proved unreliable due to processing discrepancies at the tape 
boundary areas. 

Speed Profiles 
Speeds were computed by a data processing program in miles per 

hour for stationing along a roadway. A negative stationing value was 
used to tie the profile to actual physical locations on the roadway. 
This permitted plots to be made of actual speed profiles through the 
traffic control zones. Typical plots are illustrated in Figures 24 
through 27. 

Highway organizations normally have restrictions on the hours of 
the day a road can be occupied. As a result, most of the speed pro- 
files were collected during moderate traffic volume conditions. Figure 24 
shows the profile of speeds when two lanes out of four on an eight-lane 
freeway were blocked. A slight drop in the speed is discernible but it 

87 



Table 13. Example of computer generated 
speeds developed from field tapes 



FREMUK 


PAVEMENTS 




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is nominal. 

In Figures 25 and 26, a two-lane closure on a six-lane divided 
facility is illustrated. The period covered from 11 A.M. to 3 P.M. 
The control zone was in the P.M. peak direction. As volumes increased 
in the late afternoon, the impact of the closure grew more pronounced. 
The profile shown in Figure 27 is typical of a four-lane facility 
where one lane is closed for maintenance. 

5 Traffic Zone Assumptions 
Based on the speed profiles developed during the study, a profile 

configuration for a traffic control zone was established. It is illus- 
trated in Figure 28. Traffic is assumed to operate at approach speed 
(AS) up to point B, travel through the influence zone at speed ZS, and 
then return to speed AS on the freeway. The transition speed from A to 
B and from B to C and D to E are assumed to make up a speed change cycle, 
The magnitude of the speed change SC is equal to 1.5 times the speed 
difference (AS - ZS) or 

SC = 1.5(AS-ZS) 
When a determination is made of the change in vehicle operation cost, 
it consists of the following: 

CN = Operation cost for a vehicle going through the 
influence zone at speed AS 

CR = Operation cost for a vehicle going through the 
influence zone at speed ZS 



94 




DISTANCE 



B 



Figure 28. Schematic speed profile of unqueued traffic 
operation through a traffic control zone 



95 



CSC = Speed change cost for a vehicle to decrease from an 
initial speed of AS to a speed (AS-SC) and return to 
speed AS 

OC = Operation cost change resulting from traffic closure 

OC = CR + CSC - CN 

Queue Assumptions 
It was not possible to find a traffic closure that created a 
queue on a freeway so a series of profile runs were made in a queue 
situation created by rush hour traffic. In Figure 29 the traffic 
entering the freeway at the Route 23 interchange creates the queue 
and in Figure 30 the queue is created by Route 66 traffic. It may 
be observed that at some point in the queue, traffic comes to a stop 
or nearly stops. For this reason, it was assumed that if a queue is 
created by a traffic control zone, the speed change will be the 
Approach Speed AS. This is illustrated in Figure 31 where a queue 
is on the verge of occurring. The queue profiles as shown in 
Figures 29 and 30 suggested that a mean speed between zero and the 
speed in the influence zone would be a reasonable approximation of 
the average operation speed in the queue. This is shown as speed QS 
in Figure 32. When a queue situation exists, the computation of the 
operation cost change resulting from the traffic closure requires the 
following steps: 

CQN = Operation cost for a vehicle going through the 
queue zone at speed AS 

96 






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INFLUENCE ZONE 



ZS 



FREEWAY 







•••• • • •" — i i > h» 



DISTANCE 



Figure 31. Schematic speed profile of traffic operation through 
a traffic control zone on the verge of queuing. 



99 



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CQ = Operation cost for a vehicle going through the 

queue zone at speed QS 
OC = CR + CSC + CQ - CN - CQN 

Highway Average Speed 
The determination of the speed AS, ZS and QS are critical to the 
determination of motorist impacts. In addition to the vehicle opera- 
tion costs, speed has an influence on accidents, value of time and 
pollution. 

Speed curves that showed speed as a function of lane volume were 

(47) 
taken from the Highway Capacity Manual . The Volumes and Speeds 

developed from the field studies were overplotted on the highway 

capacity based curves for comparison and validation of the basic speed 

volume relationships. There was tremendous scatter of the speeds at 

particular volumes around the capacity manual curve, but no reason not 

to adopt the capacity manual curves. 

It was decided to structure an algorithm for inclusion in the 

computer program developed to generate motorist impacts. The speed 

algorithm is based on Figure 33 

Where 

DS = Freeway design speed 

C = Capacity of freeway or lane closure in 1000' s 

SL = Speed limit on freeway or of the lane closure 

51 = 90% of the design speed 

52 = The speed at capacity as determined by the following 

101 




LANE VOLUME V x C 



Figure 33. Relationships between design speed and capacity 



102 



function (12C + .5C 4,46 ) 
V = Any volume in 1000' s 

A 

S = Speed for a given volume-capacity ratio 

A 

It involves the following steps: 

Step 1 Design Speed Curve 

1 SI = .9DS 

2 S2 = 12C + .5C 4 * 46 

3 S3 = SI - S2 

4 S4 = (.4V-10) x V/C 

5 S5 = S3 - S4, > 

6 S6 = (V/C) 25 x S5 

7 S d = SI - S4 - S6 
Step 2 Speed Limit Curve 

8 Sj = SL x .9 - 3.6 x V/C 
Step 3 Select Minimum Speed 

9 S = Minimum between (S, or S,) 

Design Speed Curves for 70, 60 and 50 mph were developed 
following the Step 1 procedure. The resulting speed curves are shown 
in Figure 34. 

The Step 2 computation was made for speed limits of 60, 50, 40 
and 30 mph and these are shown plotted with a 70 mph design curve in 
Figure 35. The program selects the lesser of the speeds determined in 
the two steps and assigned it to a speed matrix for range of volume 
capacity ratio values. The speed matrix for an eight-lane freeway is 
illustrated in Table 15. 



103 



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60, and 50 mph where speed limit equals design 
speed 



104 



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Figure 35. Speed curves for a range of speed limits 
on a road with a 70 mph design speed 



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106 



Queue Delay 

The assumption is made that a lane closure category can handle up 
to its capacity without generating a queue. This is the area to the 
right of the capacity curve shown in Figure 36. As the demand increa- 
ses, a queue occurs which is shown as the shaded area. At tp, Y vehicles 
are being delayed. The vehicle that was added to the queue at t« will 
be delayed time X. The program performs an hourly analysis. The queue 
delay applicable to all vehicles handled by the influence zone in the 
hour is based on the relationships illustrated in Figure 37. 
Where 

CAP = Lane closure capacity in 1000' s 
Q = Queue in 1000' s 
T = Time in hours 
VOL = Demand volume in 1000' s 
Of the volume CAP passing through the influence zone in each hour, 
the delay due to queuing associated with each vehicle is the average 
delay to all vehicles during the hour. This DELAY is computed as follows 
for the three hours illustrated: 
T.l = Q.1/V0L.1 
DELAY(l) = (0 + T.l)/2 

T.2 = Q.2/V0L.2 
DELAY(2) = (T.l + T.2)/2 
DELAY(3) = (T.2 + 0)/2 



107 



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Figure 36. Demand and capacity relationships where a 
queue is created 



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TIME (HOURS) 



Figure 37. Relationship between queue delay, capacity and demand 
volume 



109 



The queue zone distance shown in Figure 32, on which normal opera- 
tion cost is based, is the product of the DELAY and the average speed 
in the queue zone. 



110 



Traffic 

Distributions 

The hourly distribution of all traffic and the distribution of traf- 
fic among six trip purposes for each hour of the day is required in the 
program. The six trip purposes required for the program value of time 
routine are as follows: 

1. Work 

2. Social -Recreational 

3. Personal Business 

4. Vacation 

5. School 

6. Commercial 

The program is supplied with default hourly distributions of traffic 
for each trip purpose in each direction as shown in Figure 38. The five 
passenger car trip purpose distributions, based on the consultant's 
origin and destination survey data, show directional differences for work 
trips and school trips only. This is the reason for not showing direc- 
tional distributions for the other trip purposes in Figure 38. The 
default commercial vehicle distribution is based on data obtained from 
the U.S. Department of Transportation 1972 Truck Weight Study. 

The program user has the option to specify any trip purpose hourly 
distribution by direction thereby overriding any of the program defaults. 
The option also is available to balance the distribution of traffic when 
no directional difference is desired for any of the trip purposes. When 
specified, this option causes both directional distributions to be aver- 
aged and the average distribution assigned to both directions. 

Ill 




VACATION TRIPS 



16 16 20 22 24 



WORK TRIPS PM PEAK DIRECTION 



r 



20 22 24 





SCHOOL TRIPS PM PEAK DIRECTION 




20 22 24 



16 20 22 24 




20 22 24 



HOUR OF OAY 



Figure 38. Hourly distributions of traffic by trip 

purpose and direction developed for use as defaults 
in program 



112 



A single set of trip purpose distributions is used for both direc- 
tions and for the initial and final year as a program default. 

For passenger car trip purposes, the default distribution is based 
on the 1972 edition of the publication Automobile Facts and Figures. By 
assuming a commercial percentage of ten percent the following default trip 
purpose distribution was created : 

Work 33.1 

Social -Recreational 18.9 

Personal Business 28.4 

Vacation 0.1 

School 9.5 

Commercial 10.0 

The assumed default value for the commercial vehicles is actually mean- 
ingless because it will be replaced by required program input. Neverthe- 
less, it is needed to satisfy data initialization requirements which 
requires a balanced trip purpose distribution. 

The required traffic input to the program includes the specifica- 
tion of an initial and final year commercial percentage of total traffic 
volume. Whatever else the user might do in terms of specifying changes 
in other trip purpose percentages, the commercial percentage is fixed 
and all distribution balancing is forced to reconcile with the speci- 
fied commercial percentage. 

Based on the hourly and trip purpose distributions, the percentage 
of the daily traffic represented by each trip purpose each hour of the 
day is established for the initial and final years in both directions. 

113 



These percentages are either adjusted to reflect an optional input dis- 
tribution of all traffic or summed for each, hour of the day to create 
a distribution of all traffic. The hourly distributions of all traffic 
created from the default distributions are shown in Figures 39 and 40. 

Once the hourly distribution of all traffic is established, the 
percentages of the daily traffic represented by each trip purpose are 
converted to percentages of the hourly traffic represented by each trip 
purpose. These initial and final year distributions are converted to 
base year and yearly increments respectively using a linear interpola- 
tion. The base year and yearly increments are used to establish the 
traffic distribution in each year of the analysis. 

Volume 
The program requires as input the initial and final year AADT and 

the initial and final year percentage of AADT in the AM peak direction. 
A linear interpolation is made between initial and final year to estab- 
lish the AADT and the percentage of AADT in the AM peak direction for 
each year of the analysis. Using these and the previously established 
hourly distribution of traffic, the hourly volumes are computed for 
each hour of the day. 

The detour route normal hourly volumes are also computed from the 
detour route AADT assuming the same distribution of all traffic and 
percentage of AADT in the AM peak direction. The default detour route 
AADT is 20,000 which may be overridden with input. 



114 



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116 



Vehicle Parameters 

The weight and cost of an average passenger car and of a composite 
commercial vehicle are required by the program to compute increased 
operating costs. 

The program computes the commercial vehicle cost and weight from 
the distribution of commercial vehicles, the average weight of each 
vehicle, and the average cost of a vehicle within that class. The 
default weights assumed by the program are taken from the U.S. Department 
of Transportation 1972 Truck Weight Study and are shown in Table 16. 

The default average purchase costs of commercial vehicles are pre- 
sented in NCHRP 33. These were updated using the cost trends shown in 
Figure 41. Program default values for vehicle weight and base purchase 
price for a passenger car-light truck composite and three classes of 
heavy trucks follows: 

FHWA Weight in Costs in 
Classification Description kips Dollars 

Passenger Car 4.2 $ 3,000 

200000 Pickup Truck 

210000 Heavy, 2-axle 4-tire truck 

220000 2-axle 6-tire truck 15.38 7,300 

322000 4-axle semi truck(2S2) 39.76 24,400 

332000 5-axle semi truck(3S2) 53.55 39,300 



117 



Table 16. Summary of truck data developed from computer 
printout developed by FHWA from the U.S. 1972 Truck 
Weight Study 



Description of Sample 



*FHWA Truck Classification 





Location 


200000 


210000 


220000 


322000 


332000 


1. 


Calif. Sta. 001 

Volume Percentage 
Mean Weighted 


10.09 
6.80 


Gross 
0.89 


Weight in 

1.76 
13.24 


Kips 

0.23 
29.92 


0.42 
48.02 


2. 


Conn. Sta. 009 

Volume Percentage 
Mean Weighted 


3.36 
6.75 


0.68 
7.49 


2.97 
17.68 


4.46 
44.19 


4.81 
57.84 


3. 


Hawaii Sta. 012 

Volume Percentage 
Mean Weighted 


8.52 
5.61 


0.89 
7.58 


1.77 
15.68 


0.30 
51.07 


0.40 
69.39 


4. 


Idaho Sta. 028 

Vol ume Percentage 
Mean Weighted 


20.20 


0.16 


2.91 
12.88 


0.20 
34.67 


1.37 
50.00 


5. 


Mass. Sta. 002 

Vol ume Percentage 
Mean Weighted 


3.94 
4.84 


0.83 
6.20 


3.71 
14.97 


4.88 
36.84 


4.01 
46.36 


6. 


Mass. Sta. 006 

Volume Percentage 
Mean Weighted 


4.02 
5.22 


0.41 
6.81 


2.71 
14.99 


2.71 
39.46 


3.11 
44.79 


7. 


Mass. Sta. 012 

Volume Percentage 
Mean Weighted 


4.56 
5.08 


0.73 
8.14 


3.16 
15.05 


2.14 
35.70 


2.09 
50.77 


8. 


New Jersey Sta. 058 
Volume Percentage 
Mean Weighted 


3.47 
6.69 


1.02 
8.49 


2.76 
17.49 


2.94 
44.14 


7.25 
60.52 


9. 


New Jersey Sta. 060 
Volume Percentage 
Mean Weighted 


3.09 
7.40 


0.68 
8.79 


4.03 
17.23 


2.35 
46.29 


2.70 
60.91 


10. 


New Hamp. Sta. 012 

Volume Percentage 
Mean Weighted 


9.50 
5.45 


0.34 
7.18 


3.03 
14.64 


1.85 
35.32 


2.19 
46.86 


Summary of 10 Locations 

Volume Percentage 
Mean Weighted 


7.1 
5.98 


.67 
7.58 


2.9 
15.38 


2.2 
39.76 


2.8 
53.55 



*See Page 117 



118 



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64 



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70 



Figure 41. Price trend of commercial vehicles over a 
ten-year period (1972 Automobile Facts and Figures, 
Motor Vehicle Manufacturers Association) 



119 



Operation Costs 

In many economic analyses, tables and graphs are developed to per- 
mit a rapid computation of the operating costs associated with a range 
of vehicle speeds. These tables and graphs quickly become outdated 
as the unit price of the basic vehicle consumption parameters change. 

For this economic analysis, a series of basic consumption models 
were developed. Included are models for fuel consumption, tire wear, 
oil consumption, vehicle maintenance costs and depreciation. The models 
define changes in the consumption parameters due to roadway alignment, 
vehicle weight and running speed. The actual consumption parameter 
relationships may change in the future. However, they are not expected 
to vary as much as the unit costs which have been subject to rapid 
changes in recent years due to the energy shortage. 

The models developed for each of the consumption parameters draw 
on data presently reported in the literature 1 " . The consumption 
parameters fuel, tires, oil, maintenance and depreciation are each 
addressed separately. A relationship is established between consump- 
tion, speed and a range of alignment values for a base vehicle. Then 
consumption rates for a range of vehicles, based on weight, are related 
to the basic alignment model. Next, the relationships between con- 
sumption, speed and speed changes are determined for a base vehicle. 
Again, the consumption rates for a range of vehicles are examined and 
a relationship developed to expand the basic model to fit any vehicle 
weight category. 



120 



Fuel Consumption Models for Vertical Alignment 
Both Winfrey and Claffey have developed tables and graphs reflect- 
ing gasoline consumption in gallons per mile for a range of plus and 

(48-52) 
minus grades. Data from both sources were converted to gallons per 

hour and replotted. The basic relationships for a standard passenger 
vehicle were examined and found similar from both sources. For passen- 
ger vehicles, Winfrey made extensive use of early Claffey data. 
Therefore, it was decided to develop grade models using basic Claffey 
information. In NCHRP 13 v - ' a graph (Figure 5, page 13) is presented 
by Claffey showing actual increases of fuel consumption in gallons per 
hour for different grades at different speeds. An attempt was made to 
develop models for both positive and negative grades using this data. 
However, the effect of free rolling vehicles on negative grades could 
not be adequately accommodated so the use of this information was limited 
to developing positive grade models. 

The data presented by Claffey is for an 8-cylinder 1964 sedan with 
automatic transmission weighing 4175 pounds when loaded. The consump- 
tion rate in gallons per hour for both positive and negative grades is 
plotted for three speed curves (20, 30 and 50 mph). 

A model was developed for each of the three speed curves using a 
regression analysis to fit the following general model: 
LnY = A + BX 

To smooth the models and generalize them for the computer program 
module, both the intercept value A and the regression coefficient B 

121 



were modeled as a function of speed. The resulting set of curves 

closely duplicated the curve sets presented by Winfrey and Claffey 

for positive grades. The regression statistics for the three curves 

and coefficient models are shown in Table 17. 

The model set used to predict fuel consumption for positive grades 

is: 

F = Fuel consumption in gallons per vehicle per hour 

A = Intercept constant for positive grade fuel model 

B = Regression coefficient for positive grade fuel model 

S = Speed in miles per hour 

G = Positive grade in percent 

A = -.45 + .0214S 

B = .0348 + .02141nS 
P 

F = e (A P +B P X V 
vp 

For the negative grades it was not possible to develop a set of 
equations which adequately predicted fuel consumption because two 
different conditions exist. A vehicle can be moved by gravity alone 
or by some combination of gravity and throttle. From source data 
developed by Claffey and available to this study through Winfrey, fuel 
consumption rates in gallons per hour for vehicles operating at speeds 
below floating were shown to fall below the idling rate. Floating oper- 
ation is the maximum speed achieved on a negative grade without throttle. 
This reduced fuel consumption rate is caused by the increasing air fuel 
ratio which develops as speed increases while the carburetor operates 

122 



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123 



in the idle system range. A curve was fit to data developed by Claffey 
in NCHRP study 2-5^ ' to predict the fuel consumption rate for speeds 
below floating speed on negative grades. The model of this curve is: 

F f = 1/(1.61 + .1(S)) 
where 

F f = Fuel consumption in gallons per vehicle per hour 

S = Speed (MPH) 
A model was developed to predict floating speed by negative grade 
based on a graph published by Winfrey^ . The model is as follows: 

Sr = Float speed in mph 

G = Negative grade in percent 

S. = 3 - 7G 
f n 

The assumption is made that fuel consumption rates on negative 
grades follow the below float model until float speed is reached. 
Once the float speed is reached, the rate of fuel consumption for any 
increase in speed is equal to the rate increase on a normal tangent 
section for the same speed increment, i.e., the consumption curve paral- 
lels the normal tangent section fuel consumption curve. The use of the 
set of models for vertical alignment is graphically illustrated in 
Figure 42. 

Fuel Consumption Models for Horizontal Alignment 

Winfrey * ' found very little published information available on 
the influence of horizontal curves on fuel consumption. Consequently, 
his approach was to compute the horsepower developed on curves at 

124 



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SPEED(MPH) 



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Figure 42. Vertical alignment gasoline consumption curves 
for basic passenger car 



125 



different speeds and then base fuel consumption on comparable horse- 
power developed on level tangents and plus grades. Claffey made actual 

( 49-50) 
measurements of fuel consumption on different curves v ' . Therefore, 

the Claffey data was used to develop models of fuel consumption on hori- 
zontal curves. 

The speed-grade-fuel consumption models were based on data devel- 
oped by Claffey for a 8-cylinder 1964 sedan with automatic transmission 
weighing 4175 pounds when loaded. The horizontal curve data shown by 
Claffey for this same vehicle were used as a basis for the horizontal 
curve-speed models developed for the operating cost module. These 
curves were for a 4400 lb. weight. Therefore, the weight correction 
factor established by Claffey was used to convert the curves to be 
applicable to a 4175 lb. vehicle. The factor is 8% change in fuel 
consumption per 1000 lbs. change in vehicle weight. 

Claffey's graphs were blown up and fuel consumption rates, in gal- 
lons per mile, were scaled off of his chart for 10 mph increments of 
speed. For each horizontal curve the gallons per mile values were con- 
verted to gallons per hour. A model was developed for each horizontal 
curve using a regression analysis to fit the following general model: 
LnY = A + BX 

The models and analysis statistics are shown in Table 18. 

To smooth the models and generalize them for the computer program, 
both the A intercepts and B coefficients were modeled so that they 
could be determined for any horizontal degree of curvature. 



126 



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127 



A plot of the A intercepts against horizontal curvature suggested 
two alternate model forms which, were: 
Y = A + BlnX 
LnY = A + BlnX 

Additionally, the range of curvatures expected for the freeways 
being considered was not expected to exceed 6 degrees. Therefore, the 
data for the 90 degree curve was deleted in one set of analyses to 
determine if a better fitting model could be developed. Finally, data 
was included for zero degree curvature and weighted to force the result- 
ing model to predict the coefficients established for the level, tan- 
gent model. The models and analysis statistics are shown in Table 19. 

A plot of the B regression coefficient suggested that a curve of 
the form LnY = A + BX would provide the best fit if the 90 degree curve 
was not used. Again the zero degree curvature was added to the data 
matrix and weighted to force a fit to the curve defining the speed- 
fuel consumption relationship for level tangent sections. The results 
of this analysis also are shown in Table 19. 

Because there was no model for the B coefficient which included 
the 90 degree curve, both models 1 and 3 were not considered further. 
Both models 2 and 4 were considered and tables developed to compare the 
two. Both were deficient in predicting fuel consumption values which 
exceed the zero degree curvature base value. Based on Claffey's curves 
all fuel consumption values were the same at 10 mph and at the zero 
curvature level. Therefore, the predicted values for each curve were 
factored by the ratio of the fuel consumption rate at zero curvature to 

128 



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129 



the predicted value at 1Q mph. Following this factoring, hoth models 
2 and 4 produced the same values. Therefore, model number 2, the sim- 
pler of the two being examined, was selected for use in the module. 

The fuel consumption model set for horizontal curves is as follows: 

F = Fuel consumption in gallons per vehicle per hour 
P for passenger cars 

S = Speed (MPH) 

A = Intercept fuel model constant 

B = Model regression coefficient 

D = The horizontal curvature between zero and twelve 
degrees 



A u = -.483 - .087LnD 
-3.562 + .044D 



^h 



B h = e 

v = e (A h +B h S > 

The predicted values are shown in Table 20 and plotted in Figure 43. 

Alignment Weight Factor 

For the purpose of converting the basic passenger car model set to 
any vehicle weight class, Winfrey's level tangents table data for fuel 
consumption for 5-, 12-, 40-, and 50-kip commercial vehicles was di- 
vided by comparable 4-kip passenger car data. This produces a ratio 
for the range of speeds shown in Table 21. An examination of the ratio 
values revealed a trend reversal at both the high and low speed ends. 
Models were developed for 6 speeds examining the following equation 

forms: 

Y = A + BLnX 
LnY = A + BLnX 

130 



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Figure 43. Gasoline Consumption Curves for horizontal curves 
in 2 degree increments for basic passenger car 



132 



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133 



The statistics for the resulting weight ratio models are shown in 

Table 22. The A and B coefficients were plotted and were revealed to 

be polynominals. A polynominal regression was made to fit each of the 

coefficients and the statistics shown in Table 23. The final weight 

ratio model for converting passenger car fuel consumption is as follows: 

A = Weight Ratio Model Intercept 

B = Weight Ratio Model Regression Coefficient 

R,, = Weight Ratio Factor for Fuel 
w 3 

W = Weight in kips 

S = Speed (MPH) 

A r = l/(.46 + .0344S = .00031S 2 ) 

V 

\ 



= l/(.78 + .0437S - .00047S 2 ) 

(-A + B LnW) 
= e 



Speed Changes 
Both the Winfrey^ 48, 50 ^ and Claffey^ 49,51 ^ tables on excess gallons 
of gasoline consumed were reviewed to check their similarity. Winfrey's 
excess consumption levels were twice those of Claffey for the highest 

speed levels (50-70 mph) though they were very similar at the lower 

(53) 

levels. Winfrey's tables seemed to be based on Sawhill's data v ' 

which covered only heavy trucks and only the lower speed levels. In 
examining the Winfrey and Claffey data in relation to the Sawhill data, 
the differences were much more nominal. Therefore, because Claffey 
had developed actual field data for passenger vehicles, his data was 
relied upon to develop a set of curves for passenger cars. 

134 



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136 



The data presented by Claffey was presented in two tahles (NCHRP 

(52) 
111, Tables 7 and 8) v ' and represented the excess gallons of gasoline 

consumed per stop-go and slowdown speed change cycle for a composite 
passenger vehicle. The excess gasoline consumed for each increment 
of speed change was plotted and except for the stop value was a 
straight line. Winfrey's data suggested that the curves should be con- 
vex in shape and continuous through the stop speed change value. 
Therefore, models were developed for the 70 mph and 40 mph curves 
using a regression analysis to fit the model, Y = A + BLnX, and the 
analysis statistics for the regression models are shown in Table 24. 
The two curves fit the Claffey data quite closely and from the 
plots the relationship between the different speed curves seem approxi- 
mately constant. Therefore, it was assumed that a linear interpreta- 
tion between the A and B coefficients at the 70 and 40 mph levels 
would adequately permit the prediction of the appropriate coefficients 
for any operating speed. The following model which is plotted in 
Figure 44 resulted from this assumption: 

S = Speed in mph 

SC = Speed change in mph 

F = Excess gallons of gasoline consumed per speed change 
cycle 

A „ = -8 + .0035S 
sc 

B sc = * 91 + • 00134S 

(A sc + B sc LnSC) 

r = e 

sc 



137 



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138 



y .03 


PASSENGER 


CARS y 


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10 



30 50 

SPEED CHANGE (MPH) 



70 



Figure 44. Excess gasoline consumption for speed reductions 
for a series of initial speed curves for basic passenger 
car 

139 



Speed Change Weight Factor 

(53) 
The curves presented by Sawhill^ ' were a smooth set. The model 

relationship determined above for the composite passenger vehicle 

was plotted with the Sawhill curves and seemed to fit his series. 

Therefore, it was determined that the basic passenger car model could 

be factored to create reasonable excess consumption levels for any 

weight vehicle. 

Sawhill's fuel savings by constant-speed operation at 40 mph were 

plotted against each weight vehicle and a smooth curve developed to 

fit these points. The modeled curve follows and treats savings as 

excess consumption per speed change cycle: 

G = Gallons of gasoline consumed per speed change cycle 

W = Weight of vehicle in kips 

G = .0015 x W 1 ' 2 
The factor required to convert the base value passenger vehicle excess 
gallons prediction to a value representative of the vehicle weight class 
being considered is computed for the 40 mph condition as follows and 
applies to any initial speed level: 

G B = Gasoline consumption excess for a 4000 lb. vehicle 

G = Gasoline consumption excess tor a W lb. vehicle 
w r 

G Base " -0015 X4 1 ' 2 

G = .0015 x W 1,2 
w 

R w = G w /G Base 

R = Weight ratio factor to convert passenger car to any 



w 



vehicle weight 

140 



Alignment Models for Tire Wear 
The source curves used for the set of the tire wear models was 
developed from Winfrey's cost tables. ' His dollars of tire wear 
were first converted to .001 inches of tire wear using his indicated 
unit cost by vehicle class for .001 inches of wear. For the vertical 
and horizontal alignment curve set, the tire wear data was then con- 
verted from 1000 vehicle miles by speed to hourly time wear per hour 
per vehicle by speed. After plotting sets of curves for horizontal 
and vertical alignment, three model forms were selected for analysis. 
These were: 

1. LnY = A + BX 

2. 1/Y = A + BX 

3. LnY = A + BLnX 

The model form and statistics for the best fitting models are shown in 
Table 25 for three grades and three horizontal curvatures. The grade 
coefficients were plotted and it was determined that different linear 
models for positive and negative grades would produce a satisfactory 
set of models for the vertical alignment curve set. The resulting 
curve set which is plotted in Figure 45 is as follows: 

G = Positive grade in percent 

G = Negative grade in percent 

A„ = Positive grade model intercept) 

p ) \ 

A = Negative grade model intercept) 



141 



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40 
SPEED (MPH) 



80 



Figure 45. Vertical alignment tire wear curves 
for basic passenger car 



143 



B = Positive grade regression coefficient) 
p ) B 

B = Negative grade regression coefficient) 

T = .001 inches of tire wear per PC vehicle per hour 

S = Speed in MPH 

A = -8.26 + .095G 
P P 

A = -8.26 - .20G 
n n 

B„ = 2.23 - .015G n 

P P 

B„ = 2.23 + .070 G„ 
n n 

T v = e < A v +B v LnS > 

A plot of the horizontal coefficients revealed that the regression 
coefficient was linear while the intercept value was a curve. The 
curve was fit to the model form Y = A + BLnX and the resulting statis- 
tics are shown in Table 25. The final set of passenger car tire wear 
models developed for horizontal alignment are plotted in Figure 46 
are as follows: 

A, = Horizontal alignment model intercept 

B. = Horizontal alignment model regression coefficient 
D = Degree curvature 

S = Speed in mph 

T. = .001 inches of tire wear per PC vehicle per hour 

A h = -3.1 + .59LnD 

B h = .077 + .0023D 

< A n + B n S > 
T h = e 

144 





PASSENGER 


CARS 




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20 



40 
SPEED(MPH) 



60 



80 



Figure 46. Horizontal alignment tire wear curves for basic 
passenger car 



145 






For the purpose of converting the basic passenger car model set to 
any vehicle weight class, Winfrey's level tangents table data for the 
tire wear costs for 5-, 12-, 40-, and 50-kip commercial vehicles was 
converted to .001 inches of tire wear per hour per vehicle by weight 
and then fit to the model form LnY = A + BLnX. The resulting model 
statistics are shown in Table 26. Expanding the models and dividing 
the resulting tire wear values by the passenger car values produced 
the tire wear ratios shown in Table 27. A linear curve was fit to 
the ratio data to determine a model which could be used to produce a 
factor with which to convert a passenger car tire wear value to any 
weight tire wear. 

The linear model determined was as follows: 

R = Weight ratio factor to convert passenger car tire 



w 



wear for alignment to tire wear for any vehicle 



weight 

W = Vehicle weight in kips 

(^ = .76 + .061W 
This weight ratio is applied to a passenger car model set based on a 
weight of 4 kips. Therefore, to generalize the alignment models the 
factor must be applied to the tire wear produced by the PC model set. 
This results in the following models: 

T . R e^ + B v LnS> 

V w 



T h ■ R w e 



(A h ♦ B h S) 



146 



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148 



Speed Change Model for Tire Wear 

Winfrey's passenger care tire wear data for speed changes was con- 
verted from dollars excess cost of tire wear above continuing at 
initial speed per 1000 speed-change cycles to units of .001 inches of 
excess tire wear per cycle. Curves were plotted for initial speeds of 
40, 55, and 70 mph and regression models of the form Y = A + BLnX fit 
to the curve data. The resulting intercept and regresssion coefficients 
for each of the three initial speed-time wear models was plotted, the 
model form LnY = A + BX selected for both coefficients, and a regression 
fit developed. The model statistics are shown in Table 28 and a range 
of curves plotted in Figure 47. 

The ratio factor needed to convert the basic passenger car speed 

change curve set to any vehicle weight class was developed by taking 

Winfrey's tire wear data for the three initial speeds 40, 55, 70 at a 

40 mph speed change for 5-, 12-, 40-, and 50-kip vehicle weights and 

dividing these tire wear values by the 4-kip passenger car tire wear. 

This produced the ratios shown in Table 29. The ratio data was plotted 

and a linear curve fit to the points. This produced the following model: 

R = Weight ratio factor 

W = Vehicle weight in kips 

R = -.64 + .16W 
w 

Therefore, the final series of speed change models for tire wear 

become: 

A = Speed change model intercept 

B = Speed change model regression coefficient 

R = Weight ratio factor 

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30 50 

SPEED CHANGE(MPH) 



70 



Figure 47. Excess tire wear for speed reduction for a 

series of initial speed curves for basic passenger car 

151 



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152 



SC = Speed change in mph 

S = Initial Speed 

T = Excess .001 inches of tire wear per speed change 
cycle 

A = (-4.85 + .046(S)) 
sc 



SC 



e (-4.70 + .0417(S)) 



T_ = R (-A „ + BLnSC) 
sc w^ sc ' 

Alignment Models for Oil Consumption 
The source curves used for the set of oil consumption models was 
developed from Winfrey's cost tables/ ' His dollars of oil con- 
sumption were first converted to qjarts of oil using his indicated unit 
cost by vehicle class. For the vertical alignment curve set, the oil 
consumption was converted from consumption per 1000 vehicle miles by 
speed to' hourly consumption per vehicle by speed. After plotting sets 
of curves for all grades it was noted that the oil consumption varia- 
tion by speed was yery nominal as shown by Winfrey's tables. A plot 
of the curves revealed that not only were they not smooth but varied in 
shape for both positive and negative grades and also broke sharply at 
60 mph for the flat grades. Rather than try to fit Winfrey's data, a 
smooth curve was drawn through the zero grade and the -8% and a regression 
analysis made to fit the plotted curve. Further, the set of curves was 
assumed similar for positive and negative grades. That is, the same 
curve set applied for +8 and -8 percent grades. Figure 48 illustrates 
the assumed curves developed in the regression fit. 



153 



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SPEED(MPH) 



Figure 48. Vertical alignment oil consumption curves for basic 
passenger car 



154 



A linear model for both the A and B coefficients was established 

producing the following set of curves for oil consumption on grades: 

A = Grade model intercept 

B = Grade model slope coefficient 

G = Grade in percent 

= Oil consumption in quarts per vehicle per hour for 
p passenger cars 

S = Speed in MPH 

A v = -3.414 - .0184(ABS(G)) 

B v = .02418 + .00142(ABS(G)) 

= < A v +B v S) 
pc e 

The excess oil consumption to be associated with horizontal curva- 
ture was very small. Therefore, no curve set was developed for oil 
consumption as a function of horizontal alignment. 

For the purpose of converting the basic passenger car model set to 
any vehicle weight class, Winfrey's level tangents table data for oil 
consumption for 12-, 40-, and 50-kip commercial vehicles was divided by 
the 4-kip passenger car oil consumption for the speeds shown in Table 30, 
Table 30. An examination of the table revealed trend reversals at both 
the high and low speed ends. Considering the nominal variations in oil 
consumption, it was decided to model the 20 mph and 50 mph ratios and 
assume a linear trend for the entire range. The statistics for the 20 
and 50 mph initial speed ratio models is shown in Table 31. The A and 
B coefficients were made linear as a function of initial speed. The 
resulting set of models is as follows: 

155 



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157 



A = Intercept for weight ratio model 

B = Regression coefficient for weight ratio model 

W = Weight of vehicle in kips 

R = Weight ratio factor 

A r = .93 + .003(S) 

B r = -.0149 + -.00004(S) 

* R w = 1/(A r + B r W) 

Speed Change Models for Oil Consumption 
Winfrey's passenger car oil consumption data for speed changes 
was converted from dollars of excess cost of oil consumption above con- 
tinuing at initial speed per 1000 speed-change cycles to excess oil con- 
sumption per vehicle speed-change cycle. Curves were plotted for initial 
speeds of 40, 55, and 70 mph and the two following models examined in a 
regression analysis: 

LnY = A + BX 

LnY = A + BLnX 
The statistics for the final models are shown in Table 32. The coeffi- 
cient A was made a linear function of speed while the coefficient B was 
set at 1.8 after some trial and error computations. The resulting 
curve set which is plotted in Figure 49 is as follows: 



'Note: When the weight factor is over 50 kip, R = 3W/(30 + S) 

158 



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SPEED CHANGE (MPH) 

Figure 49. Excess oil consumption for speed reductions for 
a series of initial speed curves for basic passenger car 



160 



A = Speed change model intercept 
B = Speed change model regression coefficient 
= Excess quarts of oil consumed per vehicle per speed- 
change cycle 
SC = Speed change in mph 
S = Initial speed in mph 

A „ = -20.5 + .09S 
sc 

B sc = L8 

(A_ c + B hu(SC)) 

= e sc sc 
sc 

A factor to convert the speed change curve set for the basic 
passenger car to any vehicle weight class was needed. Winfrey's 
excess oil consumption data for the two initial speeds 40 and 55 at 
40 mph speed change for 12-, 40-, and 50-kip vehicle weights was 
divided by the 4-kip passenger car excess oil consumption. This 
produced the ratios for the speeds shown in Table 33. The ratio 
varied as a function of initial speed but because of the small dif- 
ferences in oil consumption a mean ratio was fit using the two fol- 
lowing curve forms : 

LnY = A + BX 
LnY = A + BLnX 

The statistics for the fit are shown in Table 32, and this model 
is used directly to compute the weight ratio factor (R ) for excess 
oil consumption for speed change cycles. 



161 



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162 



Alignment Models for Maintenance Cost 

The source curves used for the set of Maintenance Costs models was 

( 56) 
developed from Winfrey's cost tables/ ' His dollars of maintenance 

costs for the vertical alignment curve set was converted from costs 

per 1000 vehicle miles by speed to hourly cost per vehicle by speed. 

After plotting sets of curves for vertical alignment, two model forms 

were selected for analysis. These were: 

1. LnY = A + BX 

2. LnY = A + BLnX 

The model form and statistics for the best fitting models are shown in 
Table 34 for three grades. The grade coefficients A and B were plotted 
and it was determined that different linear models for positive and 
negative grades would produce a satisfactory set of models for the 
vertical alignment curve set. The resulting curve set is as follows: 

G = Positive grade in percent 

G = Negative grade in percent 

A = Positive grade model intercept 

A = Negative grade model intercept 

B = Positive grade regression coefficient 

r 

B = Negative grade regression coefficient 

M = Dollars of vehicle operating maintenance costs per 
P passenger car vehicle per hour of operation 

S = Speed in miles per hour 



163 



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164 



A = 5.828 + .014G ) 

A = 5.828 - .0285G 
n n 

B = 1.278 + .001G 
P P 

B n = 1.278 + .011G n 
M = e (-\ + B v LnS) 

A plot of the horizontal curves for maintenance cost revealed that 
curvature had very little influence on maintenance costs as evaluated 
by Winfrey. Therefore, it was decided not to create a maintenance 
cost model set for horizontal alignment. Figure 50 shows the vertical 
set. 

For the purpose of converting the basic passenger car model set to 
any vehicle weight class, Winfrey's level tangents table data for main- 
tenance costs for 5-, 12-, 40-, and 50-kip commercial vehicles was con- 
verted to maintenance cost per hour per vehicle and ratioed to his 4-kip 
passenger car data as shown in Table 35. A plot of the ratios revealed 
that they were a function of weight and vehicle speed and the curves 
were polynomials. A set of polynomial regressions were made for six 
speeds, the results and statistics being shown in Table 36. Each of the 
coefficients (A, B, and C) were plotted against speed, all curved slightly 
(S shape) and all reversed curvature at 20 mph. It was determined that 
a linear fit providing for the reversal would adequately predict the 
coefficients for the ratio equation. The linear models developed are 
as follows: 



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168 



S = Speed in mph 

A = Intercept coefficient for the weight ratio polynomial 

B = 1st degree coefficient for the weight ratio polynomial 

C = 2nd degree coefficient for the weight ratio polynomial 

W = Weight of vehicle in kips 

R = Weight ratio factor to convert passenger car maintenance 
cost for vertical alignment to costs for any vehicle 
weight. 

A r = .12 + .0084(ABS(S-20)) 

B r = .315 + .0021(ABS(S-20» 

C = .00438 + .000023(ABS(S-20)) 

R =A+BW=CW 2 
w r r r 

The ratio factor R reflects a value of one (1) for passenger cars 
w 

at 4 kips. To generalize the maintenance operation cost model for 

vertical alignment requires the application of the factor as follows: 

M = R e<A + B v LnS > 
w 

When W exceeds 50 the weight factor is 

RW = 4.68 + .039 x ABS(S-20) + .0772 x (W-50) 

Speed Change Models for Maintenance Cost 
Winfrey's passenger car maintenance cost data for speed changes 
was converted from dollars excess costs above continuing at initial 
speed per 1000 speed change cycles to costs per cycle and plotted for 
the three initial speeds of 40, 55, and 70 mph. The two regression 
models analyzed were: 



169 



1. LnY = A + BX 

2. LnY = A + BLnX 

The results and model form selected are shown in Table 38. 

A plot of the coefficients revealed that B was linear while A took 
the model for A = A 1 + B^nX. The A coefficient was modeled and the 
statistics are shown in Table 38. 

For the purpose of converting the basic passenger car model set to 
any vehicle weight class, costs data for the three initial speeds of 40, 
55, and 70 at a 40 mph speed change for 5-, 12-, 40-, and 50-kip vehicle 
weights were divided by the maintenance costs values for a basic pas- 
senger car. This produced Table 38. The ratio data was plotted and 
again a series of polynomial shape curves which were a function of initial 
speed and vehicle weight were revealed. Polynomial regressions on ini- 
tial speeds produced the statistics shown in Table 39. A linear model 
was computed for each of the three coefficients producing the following 
set of models for maintenance operation costs for speed changes: 

A = Intercept coefficient for the weight ratio polynomial 
B = 1st degree coefficient for the weight ratio polynomial 
C = 2nd degree coefficient for the weight ratio polynomial 
W = Weight of vehicle in kips 

R = Weight ratio factor to convert passenger car mainten- 
ance costs for speed change cycles to costs for any 
vehicle weight class. 

S = Initial Speed in MPH 



170 



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173 



A = Intercept Value for the speed change model for 
maintenance operation cost 

B = Regression Coefficient for the speed change model 
for maintenance operation cost 

M = Maintenance cost in dollars per 1000 speed change 
cycles 

SC = Speed change in mph 

A r = -.298 + .00605(S) 

B r = .3642 - .00173(S) 

C p = .00506 - .000025 (S) 

R =A+BW=CW 2 
w r r r 

A.. = 2.56 + 1.30Ln(S) 

B sc = 1.3 + .0068(S) 

M D (-A + B Ln(SC)) 
M = R e v sc sc x '' 
SC w 

Depreciation Model 
The curve set relating vehicle depreciation to speed is based on 
a revised algorithm by Winfrey which he plans on incorporating in the 
update to his book "Economic Analysis for Highways." The algorithm is 
based on assuming that the annual mileage driven is a function of the 
speed. Specifically, Winfrey starts with an assumed reference annual 
mileage of 12,000 miles for passenger cars driven at 40 mph. Next, he 
assumes that a reduction in speed will be distributed evenly between in- 
creased hours of operation and decreased annual mileage, i.e., a reduc- 
tion from 40 mph to 39 mph increases the annual hours of driving from 
300 to 303.85 hours. This produces 11,849 miles annually. The process 
requires that the new reference mileage becomes the annual mileage for 

174 



a speed of 39 mph when determining the annual mileage for 38 mph. 
The algorithm used to predict annual mileage as a function of speed 
was as follows: 

M = Annual mileage 

S = Speed in mph 

H = Annual hours driven 

1. S = 40 

2. H = 300 

3. M = S x H 

4. S = Replaced by S - 1 

5. H = ((M/S) - H)/2 + H 

6. Go to 3 

For increasing speeds above 40 mph, the fourth step in the algorithm 
is changed to add 1 mph increments, i.e. S = S + 1. Base values of 40 mph 
and 300 hours were used in the execution of this algorithm for both in- 
creasing and decreasing 1 mph increments to produce Table 40. A curve 
was fit to the data shown in Table 40 and produced the following model 
which is illustrated in Figure 51: 

M = Annual mileage for passenger cars 
a 

S = Speed in miles per hour 

NL = 1974 S" 489 
a 

In the 1969 edition of his book, Economic Analysis for Highways, Winfrey 
presents a curve relating the number of years to scrap to annual mile- 
age. The following model was developed to fit that curve. 

175 



Table 40. Annual vehicle mileage 
related to vehicle speed. 



SPEED 


MILEAI 


mph 




1 


2326 


2 


2845 


3 


3414 


4 


3902 


5 


4336 


6 


4730 


7 


5094 


8 


5433 


9 


5753 


10 


6056 


11 


6344 


12 


6620 


13 


6885 


14 


7140 


15 


7386 


16 


7625 


17 


7856 


18 


8080 


19 


8298 


20 


8511 


21 


8719 


22 


8922 


23 


9120 


24 


9314 


25 


9504 


26 


9690 


27 


9873 


28 


10053 


29 


10229 


30 


10403 


31 


10573 


32 


10741 


33 


10906 


34 


11069 


35 


11229 


36 


11388 


37 


11544 


38 


11698 


39 


11849 


40 


12000 



SPEED 


MILEAI 


mph 




41 


12149 


42 


12298 


43 


12444 


44 


12589 


45 


12732 


46 


12873 


47 


13013 


48 


13152 


49 


13289 


50 


13424 


51 


13558 


52 


13691 


53 


13823 


54 


13953 


55 


14083 


56 


14211 


57 


14338 


58 


14463 


59 


14588 


60 


14712 


61 


14834 


62 


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176 





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30 
SPEED(MPH) 



50 



70 



Figure 51. Annual vehicle miles as a function of speed 



177 



M = Annual mileage for a passenger car 

Y = Years to scrap 

Y = 47.5 - 3.88Ln(M ) 
s a 

Assuming that a vehicle will be completely depreciated at its 

scrap life permits the following depreciation model to be established: 

D = Depreciation rate per hour of vehicle operation 

S = Speed in miles per hour 

Y = Year to scrap for a passenger vehicle 

M = Annual mileage for a passenger vehicle 
a 

D p = 1/((Y S x M a )/S) = S/(Y s x M a ) 

The depreciation rate will be lower for most commercial vehicles 

because they will have larger lifetime mileages than the passenger 

vehicle. The relative lifetime mileages established by Winfrey were 

i 

used for vehicle life mileages. The passenger car lifetime mileage 

was divided by the 12-, 40-, and 50-kip vehicles lifetime mileage to 

produce a ratio. A curve was fit to the ratio values. This produced 

the following weight ratio factor to be applied to the model: 

R = Weight ratio factor 
w 3 

W = Weight in kips 

R = e (.163 - .031W) 

W 

The final depreciation model becomes: 

D = R w D n 

w p 
This model is plotted in Figure 52 for a range of vehicle weights. 



178 




40 
SPEED(MPH) 



Figure 52. Depreciation rate for a range of vehicle weights 
as a function of speed. 



179 



Value of Time 

The program computes the time lost by each vehicle through the 
influence zone as a function of normal speed, influence zone speed, 
influence zone length', and the average delay to each vehicle. The 
program also computes the amount of time lost in decelerating from^ 
and accelerating to ; the normal speed. This time is added to the 
influence zone time loss to give the total time lost by each vehicle. 
This time loss is multiplied by the volume affected to give the 
total time lost. The program assumes no time is lost for time losses 
of less than one-half minute. 

Commercial Vehicles 

The value of time for commercial vehicles is assumed to be in- 

(54) 
dependent of the amount of time loss as in NCHRP Report 33. ' The 

default value of time for commercial vehicles is 8.72 dollars per 

hour per vehicle. This value is the average of the composite vehicle 

values of time presented in NCHRP Report 33 for 1965 updated using 

the increasing operation cost per mile trends taken from Trinc's Redbook 

of the Trucking Industry, 1971 Edition, and shown in Figure 53. The 

value of commercial time may be specified by the program user through an 

optional input statement. 

Passenger Cars 
The value of time for passenger cars is based on the SRI report 
"The Value of Time Saved by Trip Purpose^ . In this study, the value 
of time is shown to be dependent on the amount of time lost and the 
average income of the motorist. 

180 




E 
<T3 

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181 



In developing value of time relationships SRI estimated benefits for 
50th percentile motorists. Further they made the analysis for two inter- 
vals of time savings. These were 5 to 15 minutes and greater than 15 min- 
utes. Further, SRI assumed that the benefits of any time savings between 
zero and five minutes were linear. 

In their development of time values, the average benefit function 
was forced to be non-negative. This resulted in a modification to their 
benefit equations. When the modified benefit equations were used in 
this study to recreate the SRI tables, there was disagreement between 
our predictions and the values published in the SRI report for benefit 
above 15 minutes. 

The modifications used by SRI in creating their tables were not 
available, so the following adjustments were made. First, the 50th per- 
centile benefit equations for the first and second time interval were 
made equal to one another at 14 minutes by adjusting the intercept value 
of the second time intervals 50th percentile benefit equation. Next, a 
similar adjustment was made to the average benefits equation set at 14.5 
minutes. These adjustments produced values that are within an accuracy 
of one percent of the benefit values presented in the SRI tables and are 
reproduced in Appendix C. 

The benefit values predicted using the above defined benefit equa- 
tions are expressed as dollars for given time losses. These must be 
converted to hourly rates before they can be used in the economic analysis 
to develop time costs. Additionally, to complete the "value of time" 
table matrix generated in the program, time losses greater than those pre- 
sented in the SRI report are valued at the maximum time loss rate. 

182 



Accidents 

Influence Zone Accidents 

The daily number of accidents is computed for both the normal and 
restricted conditions in the influence zone using the following equa- 
tions from NCHRP Report 47 ^ 55 ^ 
Where 

A = daily number of accidents 
SL = section length in miles 
V = annual average daily traffic volume 

a,b,& c = the constants, shown in Table 41, which 
were taken from NCHRP Report 47 

A = e (a+bLnSL+cLnV) /365 

The daily number of normal accidents in the influence zone is sub- 
tracted from the daily number of accidents computed for restricted 
conditions in the influence zone to produce an increased number of 
daily accidents. The number of increased accidents in the influence 
zone each hour is assumed proportional to the percent of daily traffic 
volume occurring in the hour. 

Speed Change Accidents 
The accidents occurring during the deceleration from the normal 

speed to the reduced speed through the influence zone are estimated using 

the following model, based on the data presented by Clinton L. Heimback 

and Harold D. Vick/ 56 ^ 



183 



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184 



AR = accident rate in accidents per million 
vehicle miles 

AC = absolute value of the acceleration rate in miles 
per hour per hour 

AR = -1.32 + .002AC 
The acceleration rate used to estimate the accident rate in this model 
is a function of the normal speed, the reduced speed and the assumed 
distance over which this change occurs. Distance assumed for the pro- 
gram is one mile. This assumption was based on a study of the speed 
profiles created during this study. 

The accident rate and traffic volume influenced is used to com- 
pute accidents. All of these accidents are counted as increased 
accidents since under normal conditions this speed change does not 
occur. 

Accident Costs 

The increased accidents in the influence zone and the accidents 
attributed to the speed change are combined to give the total increased 
accidents. These are costed using an average cost per accident. 

The average cost of an accident used as a default in the program is 

based on the data in the 1971 edition of Accident Facts published by 

(57) 
the National Safety Council/ ' This average cost is a weighted aver- 
age cost of fatal, personal injury and property damage only accidents. 
It includes insurance administration costs, medical costs, property 
damage costs, and estimated wage losses. Damages awarded in excess 
of direct costs, police and fire protection, court costs, and indirect 

185 



costs to employers are not included. The program user may specify 
a different average accident cost using an optional input statement, 



186 



Pollution 

Motor vehicle operation is a major source of carbon monoxide, 
hydrocarbons, and nitrogen oxides. The exhaust emissions of carbon 
monoxide and hydrocarbons vary considerably with speed for gasoline 
motor vehicles. The U.S. Environmental Protection Agency has de- 
veloped speed adjustment graphs for carbon monoxide and hydrocarbon 
exhaust emission factors for rural and urban travel. ^58/ These 
have been reproduced and are shown in figures 54 and 55. These 
factors were developed to correct emission for a composite group of 
vehicles operating at speeds other than some assumed average. In 
the analysis of the effect of roadway occupancy on pollution, these 
graphs are modeled and are used to develop measures of the relative 
change in emission rates for carbon monoxide and hydrocarbons as a 
percentage of non- roadway occupancy conditions. Following is shown the 
emission factors for gasoline-powered motor vehicles. The 1974 
figures were used to establish weighting for the two speed related 
emissions, carbon monoxide and hydrocarbons. 

CO HC Total 
Urban 49.7 5.28 54.98 

Rural 28.0 3.72 31.72 

The composite percentage developed in analysis reflects a weighting 

of 89% CO and 11% HC. 

Regression curves were developed for both the rural and urban 

curves shown in both figures 60 and 61 and the resulting statistics 

are presented in Table 42. The coefficients of the regression curves 

for urban and rural highways were averaged to produce the model curves 

187 




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190 



also shown in Figures 54 and 55. These models were used in the program 
to predict a pollution factor for both CO and HC for both normal and 
roadway occupancy situations. A composite factor was developed for both 
related emissions based on a weighting of 89% CO and 11% HC. As an ex- 
ample, the following computations are made when freeway traffic is forced 
to slow down to pass through a freeway influence zone: 
S = Normal hourly average speed on freeway 
S = Hourly average speed in the influence zone 
P = Pollution factor for normal operation on the freeway 

P = Pollution factor for operation in the influence zone 
r 

VM = Increased vehicle miles of pollution 

P = W 1 - 193 " - 032S n» + .lie'- 957 " - 026S n> 
n 

P = .89e (1 * 193 ■ - 032 V + .lle ( ' 957 " - 026 V 
r 

A unit was needed to express the impact of roadway occupancy on 
pollution. The measure selected was days of equivalent normal freeway 
emissions. These units are determined in the following manner: 

V = Volume of traffic passing through influence zone in 
analysis hour 

Z = Length of influence zone in miles 

VM = Added vehicle miles at normal emission level 

VM = (P /P -1)xVxZ 
v r n ' 

The increased vehicle miles of pollution VM represents the traffic 
which would need to be added and operated on the freeway under normal 
conditions to produce the additional emission resulting from the 
reduction in vehicle speed produced by a freeway occupancy. 

191 



The total vehicle miles of additional pollution are totaled by 
activity and closure category for each analysis year. Then the ve- 
hicle miles are divided by the projected average daily vehicle miles 
to produce increased pollution days. 



192 



SUMMARY 

A number of basic relationships and models have been established 
for use in a computer program which was designed to perform an Economic 
Analysis of Roadway Occupancy for Maintenance and Reconstruction 
(EAROMAR). A schematic illustration of the computer program EAROMAR 
is shown in Figure 56 where the broad program flow is illustrated. The 
program can be divided into four functional blocks which are: 

1. initialization routine 

2. pavement design interfacing 

3. maintenance module 

4. motorist module 

The initialization block makes use of many basic relationships, models 
and data which are built into the program to create a series of data 
matrices which are needed in the execution of the Drogram. The design 
interfacing block, as shown in Figure 56, interfaces with a pavement 
systems design program. This interface can occur annually. It permits 
information on traffic volume and/or pavement deterioration which is 
generated by the pavement design program to be used in the economic 
analysis. The design interfacing block also computes annual mainten- 
ance workload, establishes rehabilitation requirements, and it 
summarizes economic parameters generated by the analysis for transfer 
to the pavement systems design program or for direct output in a 
print routine. 

The maintenance block simulates the occupancy of a roadway by work 
crews and establishes activity costs together with roadway occupancy 

193 



p 



EAROMAR 



INITIALIZATION 



L. 



PAVEMENT DESIGN 

SYSTEMS PROGRAM 
1 



DESIGN 
INTERFACING 



1 



MAINTENANCE 



MOTORIST 



Figure 56. Broad program flow of EAROMAR showing 
the relationship between program blocks and the 
pavement design systems program 



194 



hours. These occupancy hours are used in the motorist block, to deter- 
mine the motorist costs associated with the roadway occupancy. These 
costs include vehicle operation costs, time costs, and accident costs. 

EAROMAR is designed to permit an evaluation of the costs generated 
by a pavement design over its life for pavement maintenance and rehabili- 
tation together with the traffic related costs created when the pavement 
is occupied and normal traffic flows are interrupted. To facilitate 
the use of EAROMAR, most of the data and all of the basic relationships 
and models needed to execute the program are included as program defaults, 
However, the program design permits a user to override essentially any 
default included in the program. These override options are illustrated 
in the detailed description of each program block which follows. 

The initialization block consists of three subroutines called 
INITAL, OPPARA and RPRINT. A flow diagram of the block is shown in 
Figure 57. In Table 43 each of the following block functions is sum- 
marized in terms of program default parameters and user optional input 
overrides J 

1. The traffic volume, directional split and commercial per- 
centage must be input to the program by the user for both the 
initial and final analysis year. The program computes values 
for each of these parameters by year based on a linear inter- 
polation. 

2. The pavement, freeway and analysis requirements must be input 
to the program by the user. The pavement is described as 
either Portland cement concrete, bituminous or composite and 

195 



r 



INITAL 



Define freeway 

traffic for 

analysis period 



Define pavement, 

freeway, and 

analysis period 



Compute 2 sets of 1000 
random worksite sizes 
and 1000 random 
sequenced road locations 



Compute simulation 

workload for up 

to seven activities 



Compute a speed 

matrix for each 

feasible lane closure 



L 



Establish allowable 

roadway occupancy hours 

for seven activities 



Develop an hourly traffic 

distribution matrix by 

trip purpose, direction 

and analysis year 



OPPARA 



Create an operation costs 
matrix for passenger cars 
and commercial 
vehicles by speed 



Create a value of time 

matrix by time loss 

and passenger 

car trip purpose 



RPRINT 



Display program 
assumptions 




Figure 57. A flow diagram of the initialization block 
of program EAR0MAR which includes subroutines 
INITAL, OPPARA and RPRINT 



196 



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197 



the pavement thickness is described by its surface, base and 
subgrade thickness. The freeway can be 4-, 6-, or 8-1 ane 
divided and any length and analysis period can be specified. 

3. The computer program uses a random number generating algorithm 
and two worksite size density distributions to produce a matrix 
of random worksite sizes and roadway locations. One thousand 
worksite sizes are established for each of the two density dis- 
tributions and the 1000 random roadway locations are sorted in 
ascending order. 

4. The computer program computes a simulation workload for each 
of seven activities based on the magnitude of the workload 
at each worksite and the number of iterations specified for 
the simulation process. 

5. The computer program makes use of a traffic volume/capacity 
ratio-speed algorithm to compute a ten point speed matrix for 
each feasible freeway lane closure condition. The algorithm 
is based on the freeway design speed and each lane closure 
capacity and closure speed limit. 

6. Based on a definition of the first and last hours of each 
occupancy interval for each of seven activities, the computer 
program creates a matrix of available occupancy hours for 
each activity. 

7. The computer program combines the required traffic input with 
any input options, fills in the voids with program assumptions 
and then creates a balanced matrix of the hourly distribution 

198 



of traffic by trip purpose, by direction for a base year period 
and a yearly increment. 

8. The computer program uses the value of time algorithm developed 

(27) 
by SRI v '.along with income level and vehicle occupancy for 

work and school trips and computes a matrix of the value of 

time by time loss and by passenger car trip purpose. 

9. The computer program contains a series of vehicle operation 
consumption models for fuel, oil, tires, vehicle maintenance 
and vehicle depreciation. The models predict consumption rates 
as a function of vehicle speed and pavement vertical and hori- 
zontal alignment for a 4000 lb. passenger car. The consumption 
rate b/ speed is factored to reflect the weight of a typical 
passenger car and a composite commercial vehicle. Unit costs 
are applied to the resulting consumption values to create a 
vehicle operation costs matrix for passenger cars and commer- 
cial vehicles as a function of speed. 

10. All program inputs, assumptions and generated matrices pertinent 

to the economic analysis are displayed in a computer printout. 
The pavement systems design interfacing block controls the analy- 
sis process. This block's function is handled by subroutine YEAR in 
program EAROMAR. A diagram of the program flow process in subroutine 
YEAR is shown in Figure 58. The applicable defaults and user input 
options for overriding program defaults are summarized in Table 44. 
The functions performed by YEAR are the following: 

199 



r 



YEAR 



Establ ish annual 
traffic volume, 
split and commercial 



Determine 
pavement PSI 



Establish 
analysis 
age 






Test for 
rehabilitation 







Determine annual 
workload for 
each activity 



Establ ish 

directional traffic 

volume for year 



Establ ish 
speed matrix 
for the year 



Go to 

maintenance 

block 



Go to 

motorist 

block 



L 



Output summary 

of economic 

analysis 



Figure 58. A flow diagram of the design interfacing block of 
program EAROMAR which is called subroutine YEAR 



200 



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201 



1. The base year array and yearly add-on increment array created 
in the initialization bloclc for: the volume of traffic, the 
hourly distribution of traffic by trip purpose, the direction- 
al split of traffic, and the commercial percentage of total 
traffic are added together for each analysis year. 

2. The pavement's present serviceability index (PSI) is established 
for each analysis year through direct interface with the pave- 
ment systems design program or through a computation which 
considers the accumulated 18-kip axle loadings. 

3. An analysis age is established based on the pavement's PSI. 
The analysis age is used in workload models which assume a 
pavement service life of 20 years. 

4. The pavement PSI is compared with a specified terminal PSI 
value. When the pavement PSI becomes less than the terminal 
PSI value, rehabilitation is specified in the analysis year. 

5. A series of activity workload models applicable to port! and 
cement concrete, bituminous or composite pavements are used 
annually to compute maintenance activity workload. 

6. An hourly directional traffic volume matrix is determined 
annually based on the annual volume, directional split and 
a hourly distribution matrix. The hourly volume is tested 
against capacity and modified anywhere the volume-capacity 
ratio is exceeded. 

7. A directional speed is determined for each hour based on the 
speed matrix and the hourly volume-capacity ratio. 

202 



8. The subroutine MAINT is called and the occupancy of the roadway 
is simulated for each, activity having a workload in the analysis 
year. For eyery feasible lane closure, the hours of roadway 
occupancy are established and placed in an array to be used in 
MOTOR. Also, maintenance costs are computed for each closure 
category and held in a print array. 

9. The subroutine MOTOR is called and the motorist operation costs, 
time and time costs, accidents and accident costs, and pollution 
days are computed for each closure category and held in a print 
array. 

10. The print array containing maintenance and motorist data is sum- 
marized by closure category for each direction and year, the 
minimum cost closure category is selected for each activity, 
summarized for all activities and discounted to present worth 
dollars and accumulated for a year to date total. 
The maintenance block is subroutine MAINT which simulates the occu- 
pancy of the roadway by work crews. A diagram of the subroutine is 
shown in Figure 59. The prdgram defaults and optional user inputs are 
summarized for the following functions in Table 45 : 

1. The workload and maintenance level for each activity is tested 
to determine if it will be performed in the analysis year. 

2. The simulation parameters worksite type, random or uniform spac- 
ing and the number of simulation iterations are established for 
the activity. 

203 



I 

Determine the time 
required for crews 
to perform work 




Determine 
simulation 
parameters 



Establish the 

workload at 

each worksite 



L 



Determine the 

available roadway 

occupancy hours 



Establ ish workzone 
average length 



Accumulate workcrew 
occupancy hours 
by lane closure 



Compute activity 

annual costs by 

closure category 



Figure 59. A flow diagram of the maintenance block of program 
EAROMAR which is a subroutine named MAINT 



204 



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205 



3. The magnitude of the activity workload is determined at each 
roadway location. 

4. The available roadway occupancy time is determined based on 
specified work hours, volume/capacity ratio constraints 
together with crew and activity requirements. 

5. The amount of time required for work crews to complete work at 
a given location is computed and performed if sufficient occu- 
pancy time is available. 

6. The average workzone length for an activity is determined for 
all workzones used in the simulation process. 

7. The actual roadway occupancy hours are accumulated in days 
of each hour for each feasible lane closure. 

8. The total activity crew hours are costed for the annual work- 
load and held in a print array by road closure category. 

The motorist block generates the traffic warrants. These warrants 
consist of operation, time and accident costs together with lost time, 
accidents and pollution impacts. A subroutine called MOTOR performs 
the traffic warrants analysis and a diagram of this subroutine is shown 
in Figure 60. The defaults applicable to MOTOR and the user input 
options available to modify the analysis process are shown in Table 46. 
These are summarized by the following subroutine steps: 

1. The hourly capacity of each lane closure is computed as a 

function of lane closure capacity, shoulder capacity and 

percentage of trucks in the traffic stream. 

206 



r 



MOTOR 



Establ ish the 

capacity of 

each lane closure 



Determine detour 

parameters 

and capacity 



Establ ish motorist 

impact duration 

for each lane 

closure and activity 



i 



Establish speed, 

volume and delay 

by hour for each 

lane closure 



i 



Accumulate operation 

costs for lane 
closure and activity 



L 



Accumulate time 

loss and time 

costs for lane 

closure and activity 



Accumulate 

accidents and 

accident costs by 

lane closure 

and activity 



Accumulate pollution 

days by lane closure 

and activity 



Compute 


annual 


activity 


operation 


costs, 1 


ost time, 


time costs, 


accidents, 


accident 


costs and 


pollution days by 


closure 


category 



Figure 60. A flow diagram of the motorist block of program 
EAROMAR which is a subroutine named MOTOR 



207 



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208 



2. The detour parameters and capacity are given program values. 

3. The motorist impact duration for each roadway occupancy is 
determined by examining the occupancy matrix generated by MAINT, 

4. The speed for each hour of roadway occupancy is determined 
using the speed matrix and a computed hourly volume/capacity 
ratio, the volume is limited to the capacity in any given hour 
and the delay is based on queues which develop when the actual 
hourly volume exceeds the capacity for the lane closure. 

5. The increase in vehicle operation costs is determined by taking 
the difference in operation costs and speed change costs for 
each closure and the comparable normal operation costs in 

the hour. 

6. The loss time is based on the difference between normal opera- 
ting speed and lane closure operation speed plus any delays 
created when queues occur. The losses by hour by vehicle trip 
purpose are used with the value of time matrix to generate time 
costs. 

7. Accident rates are computed for each lane closure as a function 
of lanes and deceleration rate, subtracted from normal rates 
which are a function of lanes and costed. 

8. Pollution days are based on the number of days required to 
create pollution levels during normal operation equal to the 
increased pollution created by a lane closure. 



209 



9. The lane closure created operation costs, time losses and costs, 
accidents and accident costs and pollution days are grouped for 
closure categories, and placed in a print array to be displayed 
by subroutine YEAR. 
As designed, the computer program EAROMAR permits traffic warrants 
to be developed for premium pavements. The warrant as a minimum will be 
based on the pavement design and traffic volume parameters specified by 
the user of the program together with program default data based on 
assumptions reflecting best present estimates. 

A program run can be tailored by a user to fit any specific condi- 
tion. Further, a computer run can vary from evaluating a single work 
activity in one year to evaluating up to seven activities for a multiple 
number of years. 



210 



RESULTS 

Six demonstration runs were made using the program EAROMAR, an 
Economic Analysis of Roadway Occupancy for Maintenance and Reconstruc- 
tion. A different pavement type was specified for each demonstration 
run. The six pavement types were 8-, 6-, and 4-1 ane bituminous con- 
crete and 8-, 6-, and 4-1 ane portland cement concrete. The required 
program input as specified for each of the six pavement types is shown 
in Table 47. 

All of the program default values were used in each demonstration 
run. The defaults are summarized in Volume II. 

The results in terms of present worth costs are shown in Table 48. 

The discontinuity in the maintenance and rehabilitation requirements 
for the bituminous pavements results from the rehabilitation requirements 
Resurfacing occurs for the first time in the 8th, 10th and 12th years 
for the 8-, 6-, and 4-lane pavements respectively. With the portland 
cement concrete, all resurfacing occurs in the 17th year. 

The accident costs are essentially a function of traffic volume. 
The operation and time costs are related to workload, traffic 
volumes and queues. 

From Table 48, the total costs for the 8-, 6-, and 4-lane bituminous 
pavement reduce to $7.04, $7.36 and $17.62 respectively per square yard 
of pavement. The comparable costs for the 8-, 6-, and 4-lane portland 
cement concrete pavements are $1.88, $3.31 and $7.94 respectively per 
square yard of pavement. 

211 





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213 



REFERENCES 

1. Hudson, W. Ronald and Kennedy, Thomas W., "Parameters of Rational 
Airfield Pavement Design System." Transportation Engineering 
Journal of ASCE, Vol. 99, No. TE2, May 1973 

2. Hudson, W. Ronald, McCullough, B.F., Finn, Fred N., "Factors 
Affecting Performance of Pavement Systems." Transportation 
Engineering Journal of ASCE, Vol. 95, No. TE3, Proceedings Paper 
6740, August 1969, pp. 505-519. 

3. Hudson, W. Ronald, et al . , "A Systems Approach Applied to Pavement 
Design and Research." NTIS Publication No. PB 192 937, March 1970 

4. Hudson, W. Ronald, Kher, Ramesh K., McCullough, B. Frank, 
"Automation in Pavement Design and Management Systems." Paper 
presented at Highway Research Board Summer Meeting, August 16- 
18, 1971. 

5. Darter, Michael I., Hudson, W. Ronald, Haas, Ralph C. F., "Selection 
of Optimal Pavement Designs Considering Reliability, Performance, 
and Costs." Paper presented at 53rd Annual Meeting of Highway 
Research Board, January 1974 

6. Kher, Ramesh K. , Hudson, W. Ronald, McCullough, B. Frank, "Com- 
prehensive Systems Analysis for Rigid Pavements." Highway Research 
Record, No. 362, pp. 9-20. 

7. Kher, R. K., McCullough, B. Frank, Hudson, W. Ronald, "A Sensitivity 
Analysis of Flexible Pavement System FPS2." NTIS Publication No. 

PB 213 736, August 1971. 

8. Kher, Ramesh, Hudson, W. Ronald and McCullough, B. Frank, "A 
Working Systems Model for Rigid Pavement Design." Hiqhway Research 
Record, No. 407, 1972, pp. 130-145. 

9. Lytton, R. L., McFarland, W. F., "Systems Approach to Pavement 
Design — Implementation Phase." Final Report Draft prepared for 
Highway Research Board, March 1974. 

10. McFarland, William F., "Benefit Analysis for Pavement Design Systems. 
Research Project 1-8-69-123, Texas Transportation Institute, Center 
for Highway Research, April 1972. 

11. "Investment Strategies for Developing Areas: Highway Cost Model 
Operating Instructions and Program Documentation," prepared for 

U. S. Department of Transportation, Office of International Programs, 
Technical Assistance Division, by Fred Moavenzadeh, Martin Becker, 
Thomas Parody, Massachusetts Institute of Technology, January 1973. 

214 



12. Moavenzadeh, F., "Investment Strategies for Developing Areas: 
Analytic Model for Choice of Strategies in Highway Transportation." 
Research Report No. 72-67, Massachusetts Institute of Technology, 
June 1972. 

13. Alexander, J. A., Moavenzadeh, F., "Highway Maintenance." Report 
No. TR-70-38 Urban Systems Laboratory, Massachusetts Institute 

of Technology, September 1970. 

14. Findakly, Hani, Moavenzadeh, F. , Soussou, Joseph, "Stochastic 
Model for Analysis of Pavement Systems," Transportation Engineering 
Mournal of ASCE, Vol. 100, No. TE1, February 1974, p. 57. 

15. Lemer, A. C, and Moavenzadeh, F. , "Reliability of Highway Pavement." 
Highway Research Record, No. 362, 1971, pp. 1-8. 

16. Alexander, John A. and Moavenzadeh, Fred, "Predicting Maintenance 
Cost for Use in Trade-off Analyses." Highway Research Record No. 
391, 1972, pp. 1-9. 

17. Alexander, John A., "Application of Maintainability and Expected 
Cost Design Analysis to Highway Design." Paper presented at 
Highway Research Board Summer Meeting, Olympia, Washington, August 
1973. 

18. "Investment Strategies for Developing Areas: Analytic Model for 

Choice of Strategies in Highway Transportation." Department of 
Transportation Report No. D0T-0S-00096, January 1973. 

19. Lemer, A. C, and Moavenzadeh, Fred, "An Integrated Approach to 
Analysis and Design of Pavement Structure." Highway Research 
Record, No. 291, 1969, pp. 173-185. 

20. Both, G. J., Thompson, K. E., Lack, G. H. T. , "The Evaluation of 
Rural Road and Bridge Improvements," paper No. 810, Proceedings of 
the Australian Road Research Board Conference, Volume 6, Part 2, 
1972, pp. 145-171. 

21. Hutchinson, B. F., "A Conceptual Framework for Pavement Design 
Decisions." Highway Research Record, No. 21, 1966, pp. 1-14. 

22. Hutchinson, B. F., and Haas, R. C. F., "A Systems Analysis of the 
Highway Pavement Design Process." Highway Research Record, No. 239, 
1968, pp. 1-14. 

23. Haas, Ralph, "General Concepts of Systems Analysis as Applied to 
Pavements." Paper presented at Annual Meeting, Highway Research 
Board, Washington, D. C. , January 1974. 

215 



24. Phang, W. A., "Flexible Pavement Design in Ontario," Paper 
presented at Highway Research Board Annual Meeting, Washington, 
D. C, January 1974. 

25. Phang, W. A. and Slocum, R., "Pavement Investment Dei ci si on-Making 
and Management System." Highway Research Record No. 407, 1972, 
pp. 173-194. 

26. "Interstate Highway Maintenance Requirements and Unit Maintenance 
Expenditure Index." NCHRP Report 42, Highway Research Board, 1967. 

27. Thomas, Thomas C, and Thompson, Gordon I., The Value of Time 
Saved by Trip Purpose." Stanford Research Institute, SRI Project 
MSU-7362, October 1970. 

28. Stott, J. P., and Brook, K. M., "Report on a Visit to U.S.A. to 
study Blow-ups in Concrete Roads." Road Research Laboratory Report 
LR128, 1968. 

29. Oehler, L.T., Holbrook, L.F., "Performance of Michigan's Postwar 
Concrete Pavements." Research Report R-711, Michigan State Highway 
Commission, June 1970. 

30. "A Study of Blowups in Rigid Pavements in Illinois," State of 
Illinois Department of Public Works and Buildings, Division of 
Highways, Research and Development Report No. 18. 

31. Hensley, M. J., Staff Engineer, "The Study of Pavement Blowups." 
Research Project 10, Arkansas State Highway Department Planning 
and Research Division, January 1966. 

32. Bowers, David G., "A Study of the Failures Occurring in the Concrete 
Pavement of the Connecticut Turnpike and Roads of Similar Design." 
Division of Research and Development, Connecticut State Highway 
Department, June 1966. 

33. Foxworthy, Paul T. , "Statewide Survey of Blowups in Resurfaced 
Concrete Pavements." Joint Highway Research Project, Number 3, 
Purdue University and Indiana State Highway Commission, February 
1973. 

34. "Arizona Maintenance Management Research and Development Study," 
Final report, June, 1972, Roy Jorgensen Associates, Inc. 

35. "The Cost of Constructing and Maintaining Flexible and Concrete 
Pavements over 50 Years." Road Research Laboratory, Crowthorne, 
England, RRL Report LR 256, 1969, NTIS Publication No. PB 185 268. 

36. "Performance Budgeting System for Highway Maintenance Management 1 .' 
National Cooperative Highway Research Program Report No. 131, 1972. 

216 



37. "Development and Implementation of a Maintenance Management System 
for the Nevada Department of Highways." Final Report, July 1974, 
Byrd, Tall amy, MacDonald and Lewis. 

38. "Long Range Pavement Maintenance Program." Supplemental Report 
No. 2. Byrd, Tall amy, MacDonald and Lewis for the Illinois State 
Toll Highway System, 1971. 

39. "Illinois State Toll Highway System. . .Long Range Pavement Maintenance 
Program." Bertram D. Tallamy Associates for the Illinois State 

Toll Highway Commission, March 1968. 

40. "Long Range Pavement Maintenance Program." Supplemental Report No. 1, 
Byrd, Tallamy, MacDonald and Lewis for the Illinois State Toll 
Highway System, 1969. 

41. "The AASHO Road Test, Report 5, Pavement Research." Highway 
Research Board Special Report 61E, Publication No. 954, 1962. 

42. "Heavy Maintenance Requirements --John F. Kennedy Expressway." 
Bertram D. Tallamy Associates for the Division of Highways, 
Department of Public Works and Buildings, State of Illinois, 
November 1967. 

43. "Heavy Maintenance Requirements—Calumet Expressway." Bertram 

D. Tallamy Associates for the Division of Highways, Department of 
Public Works and Buildings, State of Illinois, November 1967. 

44. "Heavy Maintenance Requirements--Dan Ryan Expressway." Bertram D. 
Tallamy Associates for the Division of Highways, Department of 
Public Works and Buildings, State of Illinois, November 1967. 

45. Peterson, Dale E., et al . , "Evaluation of Pavement Serviceability." 
Utah State Department of Highways, Materials and Tests Division, 
1973, NTIS Publication No. PB 224 894/6. 

46. "Progress Report of an HRB-AASHTO Joint Study of Maintenance and 
Operations Personnel." Highway Research Circular No. 153, 
December 1973. 

47. "Highway Capacity Manual -1965. " Highway Research Board Special 
Report No. 87, Publication No. 1328, 1965. 

48. Winfrey, Robley, "Economic Analysis for Highways." International 
Textbook Company, Scranton, Pennsylvania, 1969, 923 pp. 

49. Claffey, Paul J., "Time and Fuel Consumption for Highway User 
Benefit Studies." Highway Research Board Bulletin No. 276, 
1960, pp. 20-34. 



217 



5Q. Winfrey, Robley, "Research on Motor Vehicle Performance Related 
to Analyses for Transportation Economy." Highway Research Record 
No. 77, 1965, pp. 1-18. 

51-. "Running Cost of Motor Vehicles as Affected by Highway Design- 
Interim Report." National Cooperative Highway Research Program 
Report No. 13, 1965, 43 pp. 

52. "Running Costs of Motor Vehicles as Affected by Road Design and 
Traffic." National Cooperative Highway Research Program Report 
No. Ill, 1971, 97 pp. 

53. Sawhill , Roy B., "Motor Transport Fuel Consumption Rates and 
Travel Times." Highway Research Board Bulletin No. 276, 1960, 
pp. 35-91. 

54. "Values of Time Savings of Commercial Vehicles." National 
Cooperative Highway Research Program Report No. 33, 1967. 

55. Kihlberg, Jaakko K. , Tharp, K. J., "Accident Rates as Related to 
Design Elements of Rural Highways." National Cooperative Highway 
Research Program Report No. 47, 1968. 

56. Heimback, Clinton L. and Vick, Harold D., "Relating Change of 
Highway Speed per Unit of Time to Motor Vehicle Accident Rates." 
Highway Research Record No. 225, 1968. 

57. "Accident Facts--1971 Edition." National Safety Council, Chicago 
Illinois. 

"Compilation of Air Pollutant Emission Factors," U. S. Environmental 
Protection Agency, February 1972, NTIS Publication No. PB 209 559 



218 



APPENDIX A 
FIELD DATA COLLECTION 

Equipment 

The original field equipment for this study consisted of three 
cassette tape recorders, three stopwatches, and three electronic 
oscillators on which the frequency of the tone can be lowered or 
raised by closing the appropriate switches. On the observer fre- 
quency boxes both of these switches are hand-held pushbuttons. On 
the test car frequency box the switch for lowering the tone was 
replaced with photodiode circuit which is triggered by reflected 
light from one polished spot on the auxiliary speedometer cable. 

The photodiode circuit for lowering the frequency of the tone 
proved to be inadequate due to multiple reflections from the 
speedometer cable and audio ripple in the power line which caused 
erroneous low frequency tones. The reflective sensing circuit was 
replaced with a slotted optical limit switch and rotating blade attached 
to the speedometer cable to solve the multiple reflections problem. 
At the same time the tone module was replaced with an integrated 
circuit timer. Zener diode protection against voltage spikes was 
added to solve the audio ripple problem. These modifications were 
made only to the test car frequency box. The circuit diagram of 
this frequency box is shown in Figure 61. 

The tape recorders are used to record the tones from each of the 
frequency boxes. This establishes a time base for determining the 
lapse times between events which are marked with raised or lowered 
tones. 

219 




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The stopwatch is ised to manually record the total recording time 
of each run. This time is used to check and, if necessary, adjust the 
tape recorder established time base. 



221 



Data Collection 

Data was collected at a number of sites in the Washington, D. C. 
and San Francisco, California areas. Field data logs like the one 
shown in Figure 62 were made for each site. The lane closure dia- 
grams shown in Figures 63 thru 70 were drawn using these data logs 
and topographic maps of the study area. 

The field team for data collection consisted of three men, one 
test car driver and two observers. The test car driver collected 
speed profile and sign location data while the two observers collected 
volume and headway data using the following procedures; 

Sign Location Run Procedure 

1. Wind the stopwatch and reset to zero. 

2. Switch on the microphone and verbally identify the tape as a 
SIGN LOCATION RUN and then the observation site number, the 
date, and the time of day to the nearest minute. For example, 
SIGN LOCATION RUN, Observation Site Number 1, November 7, 
1973, 10:25 A.M. 

3. Switch off the microphone and pull the microphone plug from 
the tape recorder and then simultaneously switch on the 1%-volt 
switch of the frequency box and start the stopwatch. 

4. Enter the expressway. 

5. Push control button to mark the location of each traffic 
control sign, each observer, the tiedown point and all other 
features in order as described on the "FIELD DATA LOG," The 



222 



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223 



TYPICAL CROSS SECTION 6 LANE DIVIDED HWY 



WOODED MEDIAN ' 



3 LANE ROADWAY 



U 




O 

J- 



TRAFFIC CONES 
BARRELS 
OBSERVER 
SIGNS 




Figure 63. Lane closure diagram of observation site number 1, 
1-95, Prince William County, Virginia 



224 



TYPICAL CROSS SECTION 6 LANE DIVIDED HWY 



L. 



J 



T 


TRAFFIC CONES 


<8> 


BARRELS 


O 


OBSERVER 


_L 


SIGNS 




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Figure 64. Lane closure diagram of observation site number 2, 1-95 
Prince William County, Virginia 



225 



TYPICAL CROSS SECTION 4 LANE DIVIDED HWY. 



GROUND' 



WOODED MEDIAN 



▼ TRAFFIC CONES 

<g) BARRELS 

O OBSERVER 

-L SIGNS 




O 

N 



O 

or 

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or 



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Figure 65. Lane closure diagram of observation site number 3 
1-95, Stafford, Virginia 



226 



TYPICAL CROSS SECTION 4 LANE DIVIDED HWY. 

GROUND ' 



WOODED MEDIAN 



2 LANE ROADWAY 



'71 



ro 



T TRAFFIC CONES 

<8> BARRELS 

O OBSERVER 

-L SIGNS 



END 
ROAD WORK 




O 

N 



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ce 



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o 



< 
or 



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I 

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_l 
00 



Figure 66. Lane closure diagram of observation site number 4, 
Stafford, Virginia 



1-95 



227 



TYPICAL CROSS SECTION 8 LANE DIVIDED HWY. 



LANE BARRIER- 



^4 LANE ROADWAY 




LU 

o 

N 



O 



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o 

o 
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< 



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Figure 67. Lane closure diagram of observation site number 5, 
State Highway 17, Oakland, California 



228 



TYPICAL CROSS SECTION 8 LANE DIVIDED HWY. 

LANE BARRIER- 7 



GROUND - 



-4 LANE ROADWAY 




LU 

O 

N 



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or 



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Figure 68. Lane closure diagram of observation site number 6, 
(1st closure), U. S. 101, San Mateo, California 



229 




A 



TYPICAL CROSS SECTION 8 LANE DIVIDED HWY. 



GROUND < 



LANE BARRIER 



T 



X 



LANE ROADWAY 



▼ TRAFFIC CONES 

® BARRELS 

O OBSERVER 

-L SIGNS 




LU 

Z 

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M 



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or 



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o 

o 



< 



l!_ 

o 

0_ 

i 

o 

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m 



Figure 69. Lane closure diagram of observation site number 6, 
(2nd closure), U. S. 101, San Mateo, California 



230 



TYPICAL CROSS SECTION 4 LANE UNDIVIDED HWY. 



GROUND' 



t; 



2 LANE ROADWAY 




y 



T TRAFFIC CONES 

<g> BARRELS 

C OBSERVER 

JL SIGNS 



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Figure 70. Lane closure diagram of observation site number 7, 
State route 92, San Mateo, California 



231 



distance between each of these event marks will be taken from 
the tape and automatically converted to stationing to be used 
in drawing a diagram of the lane closure. The distance between 
observers will be used to calculate the speeds between observers 
Therefore, the observer locations should be marked when travel- 
ing at a slow speed or by actually stopping at each observer 
location to insure maximum accuracy. 

6. After completing the pass through the traffic control zone, 
pull the vehicle to the side of the road and stop and then 
simultaneously switch off 1^-volt switch on frequency box 
and stop stopwatch. 

7. Plug the microphone into the tape recorder, switch the 
microphone on and verbally describe the end of SIGN LOCATION 
RUN, the date, the time of day, and the elapsed time. For 
example, END SIGN LOCATION RUN, Observation Site Number 1, 
NOVEMBER 7, 1973, 10:45 A.M., lapsed time 19 minutes 

46.9 seconds." 

8. Push "STOP" button on tape recorder. 

9. Fill out "TAPE LOG" which consists of tape cassette number, 
run number (S.L.), the time of day at beginning and end of 
run, and lapsed time. 

Speed Profile Run Procedure 

When the SIGN LOCATION RUN is complete and the observers have been 
positioned on the road, the test car driver should initiate the speed 
profiles. These runs should be numbered sequentially with a complete run 

232 



consisting of as many passes AGAINST and THRU the traffic control zone 
as can be recorded on one side of a cassette tape. Further, the test 
vehicle driver will check the phasing of the observers. Both observers 
should have red hats on when they are initiating a test and off when 
they are completing a test. If the observers are out of phase the 
driver should notify them so they can get back in phase. 

1. Place the clean side of a cassette tape on the recorder and 
rewind tape to beginning. 

2. Wind and reset stopwatch. 

3. Plug the microphone into the tape recorder, turn the microphone 
on, put recorder in record mode and waste a minute of cassette 
tape to pass the leader. 

4. Verbally describe the cassette tape by run number, direction 
of first pass, date, and time to the nearest minute. For 
example, "RUN NUMBER 9 THRU traffic control, November 7, 1973, 
2:35 P.M." 

5. Turn off the microphone and pull the microphone from the 
tape recorder and then simultaneously switch on the 1^-volt 
switch on the frequency box and start the stopwatch. 

6. Enter expressway and attain normal traffic flow speed. 

7. Push control button to reference the speed profile on roadway. 
a. On THRU the traffic control zone passes, push the control 

button to indicate the passing of each observer. 

This will tie the speed profile to the observer positions 

on roadway and provide a measure of the elapsed time between 

observers. 

233 



b. On the AGAINST traffic control zone passes, push the 
control button to indicate the passing of the tiedown 
point. 

8. Estimate remaining time and when there is not enough recording 
time left on a side of the tape cassette to record the entire 
next pass, either THRU or AGAINST the traffic control zone 

he should pull the vehicle to the side of the road, stop, 
and then simultaneously switch off the 1%-volt switch on the 
frequency box and stop the stopwatch. 

9. Plug the microphone into the tape recorder, switch the micro- 
phone on and verbally describe the tape by run number, direction 
of last pass, date, time of day to the nearest minute, and 

the elapsed time. For example, "End Run Number 9, "AGAINST" 
traffic control, November 7, 1973, 3:15 P.M. elapsed time 39 
minutes 56.2 seconds. 

10. Push "STOP" button on tape recorder. 

11. Fill out the "TAPE LOG" which consists of the cassette number, 
the run number, direction of first pass, the direction of the 
last pass, the time of day the tape was started, and finished, 
and the elapsed time. 

12. Repeat steps 1-12. 



!34 



Observer Procedure 

1. Switch on the microphone and verbally describe the test run 
number, the date, and the time of day to the nearest minute, 
for example, 

Test Run No. 9, November 7, 1973, 10:30 A.M. 

2. Switch off the microphone. 

3. Put red hat on to indicate to test vehicle driver that you 
are prepared to collect data on this test run. 

4. Watch for the test vehicle; as it comes into view pull the 
microphone from the tape recorder and then simultaneously 
switch on the frequency box and start the stopwatch. 

5. As the test vehicle passes, push the red control vehicle 
button to indicate the passing of the test vehicle. 

6. Push either the red or black button for every vehicle as 
it passes. Push the red button for all control vehicles 
and the black button for all other vehicles. 

7. Remove the red hat before the test vehicle returns. 

8. When the test vehicle returns, punch the red button to indicate 
final control vehicle. This also terminates the test run. 

9. Simultaneously switch off the frequency box and stop the 
stopwatch. 

10. Plug the microphone into the tape recorder, switch the 

microphone on and verbally describe the end of the test run 
number, the date, and the time of day to the nearest minute, 

235 



and the elapsed time. For example, 

End of Test Run No. 9, November 7, 1973, 10:45 A.M., 
elapsed time 24 minutes and 22.3 seconds. 

11. Switch off the microphone. 

12. Fill out the field test run log which consists of the Test 
Run Number, the cassette number, the time of day the run 
began, and finished, and the lapsed time. 

13. Reset the stopwatch to zero for the next test run. 

14. Check cassette tape to make sure there is enough tape for 
another complete run. If not, turn cassette tape over and 
rewind or install new tape cassette. Make sure to waste 

a minute of cassette tape to pass cassette tape leader. 



236 



APPENDIX B 

A series of models was developed to predict the vehicle consumption 
parameters fuel, oil, tires, maintenance and depreciation. Tables 49 
through 67 tabulate the consumption rates for each of these parameters 
as a function of speed and vertical and horizontal alignment. 



237 



Table 49, Fuel, tires, oil, maintenance and depreciation 
in gallons, .001 inches, quarts, dollars and 
percent, respectively per vehicle hour 
for level tangent sections. 



SPEED 


FUEL 


OIL 


TIRES 


MA I NT 


DEPREC 


2 


0.65220 


0.03454 


0.00120 


0.00714 


0.00004 


4 


0,69046 


0.03625 


0.00563 


0.01731 


0.00007 


6 


0,73096 


0.03805 


0.01389 


0.02907 


0.00009 


8 


0.77383 


0.03994 


0.02635 


0.04198 


0.00010 


10 


0.81922 


0.04192 


0.04331 


0.05584 


0.00012 


12 


0.86727 


0.04400 


0.06498 


0.07049 


0.00014 


14 


0.91814 


0.04618 


0.09159 


0.08584 


0.00015 


16 


0.97200 


0.04847 


0.12329 


0.10181 


0.00016 


18 


1.02901 


0.05087 


0. 16025 


0.11835 


0.00018 


20 


1.08937 


0.05340 


0.20260 


0.13541 


0.00019 


22 


1.15327 


0.05605 


0.25049 


0.15295 


0.00020 


24 


1.22091 


0.05882 


0.30402 


0.17094 


0.00021 


26 


1.29253 


0.06174 


0.36 332 


0.18935 


0.00023 


28 


1.36834 


0.06480 


0.42848 


0.20816 


0.00024 


30 


1.44860 


0.06802 


0.49961 


0.22735 


0.00025 


32 


1.53357 


0.07139 


0.57679 


0.24690 


0.00026 


34 


1.62 352 


0.07493 


0.66013 


0.26679 


0.00027 


36 


1.71875 


0.07865 


0.74970 


0.28700 


0.00028 


38 


- 1.81957 


0.08255 


0.84558 


0.30754 


0.00029 


40 


1.92630 


0.08664 


0.94785 


0.32837 


0.00030 


42 


2.03928 


0.0 9094 


1.05659 


0.3't950 


0.00031 


44 


2.15 890 


0.09545 


1. 17137 


0.37091 


0.00032 


46 


2.28553 


0.10018 


1.29376 


0.39259 


0.00033 


48 


2.41959 


0.10515 


1.42232 


0.41453 


0.00034 


50 


2.56152 


0.11036 


1.55762 


0.43673 


0.0003 5 


52 


2.71176 


0.11583 


1.69973 


0.45918 


0.00036 


54 


2.87082 


0. 1215b 


1. 84 8 69 


0.48187 


0.00037 


56 


3.03921 


0.12761 


2.00457 


0.50480 


0.00038 


58 


3.21748 


0.13394 


2. 16 744 


0.52795 


0.00039 


60 


3.40620 


0.14058 


2.33733 


0.55133 


0.00040 


62 


3.60600 


0.14755 


2.51432 


0.57492 


0.00041 


64 


3.81751 


0. 15487 


2.69 844 


0.59873 


0.00042 


66 


4.04 143 


0. 162 54 


2.38975 


0.62274 


0.00043 


68 


4.27848 


0.17061 


3. 08830 


0.64696 


0.00044 


70 


4.52944 


0.17907 


3.29415 


0.67138 


0.00044 


72 


4.79512 


0.18 795 


3.50734 


0.695 99 


0.00045 


74 


5.0 763 8 


0.19727 


3.72791 


0. 72079 


0.00046 


76 


5.37414 


0.20705 


3.95 591 


0.74578 


0.00047 


78 


5.68937 


0.21732 


4. 19139 


0.77095 


0.00048 


80 


6.02308 


0.22309 


4.43439 


0. 79631 


0.00049 



238 



Table 50. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for tangent sections with +1% grade 



VEHICLE OPERATION PARAMETERS 
SPFEO FUEL OIL 



TIRES 



MA I NT 



2 


0.70839 


0.03401 


0.00132 


0.00724 


4 


0.76008 


0.03580 


0.00613 


0.01758 


6 


C. 81054 


0.03 ^66 


0.01505 


0.02953 


8 


0.86217 


0.03966 


0.02 847 


0.042 66 


10 


0.91583 


0.041 74 


0.04666 


0.056 76 


12 


0.97198 


0.04394 


0.06988 


0.0 7166 


14 


1.03094 


0.046 25 


0.09832 


0.08 728 


16 


1.09 301 


0.04868 


0. 13216 


0.10353 


18 


1.15842 


0.05124 


0. 17156 


0.12037 


20 


1.22741 


0.05393 


0.21665 


0. 13773 


22 


1.30024 


0.05677 


0.26758 


0.15559 


24 


1.3 7 714 


0.05975 


0.32445 


0.17390 


26 


1.45838 


0.062 90 


0.38 739 


0.19265 


28 


1.54420 


0.06620 


0.45650 


0.21180 


30 


1.63490 


0.06968 


0.53187 


0.23134 


32 


1.730 77 


0.07335 


0.61361 


0.25125 


34 


1.83210 


0.07720 


0. 70180 


0.27150 


36 


1.93922 


0.08126 


0. 79t>52 


0.29209 


38 


2.05247 


0.08553 


0.89785 


0.31301 


40 


2.17220 


0.09003 


1.00588 


0.33423 


42 


2.29880 


0.09476 


1. 12068 


0.35575 


44 


2.43265 


0.09975 


.1.24231 


0.3 7 756 


46 


2.57418 


0.10499 


1.37086 


0.39965 


48 


2.72384 


• 0.11051 


1. 50638 


0.42201 


50 


2.88209 


0. 11632 


1.64 893 


0.44462 


52 


3.04 943 


0. 12244 


1.79859 


0.46750 


54 


3.22639 


0.12837 


1. 95540 


0.49062 


56 


3.41351 


0. 13565 


2.11 944 


0.51398 


58 


3.61138 


0. 142.78 


2.29075 


0.53757 


60 


3.82063 


0.15029 


2.46938 


0.56139 


62 


4.04192 


0. 15819 


2.65541 


0.58544 


64 


4.27591 


0. 16651 


2.84387 


0.6 0970 


66 


4.52337 


0.17526 


3. 04 982 


0.63417 


68 


4.78504 


0. 18448 


3.25830 


0.65886 


70 


5.06177 


0.19417 


3.47437 


0.68374 


72 


5.35440 


0.20438 


3.69807 


0.70883 


74 


5.66 386 


0.21513 


3.92 945 


0.73411 


76 


5.99111 


0.2 2 644 


4. 16856 


0.75958 


78 


6.33716 


0.23834 


4.41544 


0.78524 


80 


6.70312 


0.25086 


4.67013 


0.81108 



239 



Table 51. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for tangent sections wttli +2% grade 



VEHICLE OPERATION PARAMETERS 
SPEED EUEL OIL 



TIRES 



MAINT 



2 


0. 74443 


0.033 48 


0.00144 


0.00735 


4 


0.81069 


0.03534 


0.00b60 


0.01 785 


6 


0.87205 


0.03731 


0.01611 


0.03000 


8 


0.93333 


0.03938 


0.03034 


0.043 36 


10 


0.99616 


0.04157 


0. 04 957 


0.0^769 


12 


1.06136 


0.04388 


0. 07404 


0.07285 


14 


1.12947 


0.04632 


0. 10393 


0.08874 


16 


1.20089 


0.04889 


0. 13941 


0.10528 


18 


1.27597 


0.05161 


0. 18065 


0.12242 


20 


1.35502 


0.05448 


O.ZZ 776 


0.14009 


22 


1.43835 


0.05 750 


0.28091 


0.15827 


24 


1.52626 


0.06070 


0. 34018 


0.1 7691 


26 


1.61906 


0.06 407 


0.40568 


0.19600 


28 


1.71707 


0.06763 


0.47 752 


0.21550 


30 


1.82061 


0.07139 


0.55579 


0.2 3 540 


32 


1.93002 


0.07536 


0.64058 


0.2 556 7 


34 


2.04567 


0.07954 


0. 73197 


0.27630 


36 


2.16793 


0.08396 


0. 83006 


0.29728 


38 


2.29719 


0.08863 


0.93490 


0.31858 


40 


2.^3387 


0.09356 


1.04658 


0.34020 


42 


2.57841 


0.09875 


1.16517 


0.36212 


44 


2.73126 


0.10424 


1.29074 


0.3 8434 


46 


2.89291 


0.11003 


1.42 334 


0.406 84 


48 


3.06389 


0.11615 


1. 56305 


0.42962 


50 


3.244 73 


0.12260 


1.70992 


0.45266 


52 


3.43601 


0.12942 


1.86401 


0.47597 


54 


3.63 834 


0.13661 


2.0253V 


0.49952 


56 


3.85234 


0.14420 


2. 19409 


0.52333 


58 


4.07872 


0. 15221 


2.37019 


0.54737 


60 


4.31819 


0.16067 


2.55373 


0.57164 


62 


4.57149 


0.16960 


2.74475 


0.59615 


64 


4.83944 


0.17902 


2. 94332 


0.62087 


66 


5.12287 


0.18897 


3. 14948 


0.6*581 


68 


5.^2269 


0.19947 


3.36326 


0.67097 


70 


5.73985 


0.21056 


3.5ti473 


0.696 33 


72 


6.07535 


0.22226 


3.81393 


0.72190 


74 


6.43 024 


0.23461 


4.05090 


0.74767 


76 


6.80566 


0.24764 


4.29568 


0.77363 


78 


7.20276 


0.26141 


4.54 830 


0.79978 


80 


7.62284 


0.2/593 


4.80883 


0.82613 



240 



Table 52. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for tangent sections with +3% grade 



VEHICLE 


OPERATION 


PARAMETERS 






SPEED 


FUEL 


OIL 


TIRES 


MA INT 


2 


0.78231 


0.03297 


0.00156 


0.00746 


4 


0.86468 


0.03490 


0.00711 


0.01813 


6 


0.93822 


0.0 3 694 


0.01 725 


0.03048 


8 


1.01035 


0.03910 


0.03 2 34 


0.04406 


10 


1.08353 


0.04139 


0.05266 


0.05864 


12 


1.15897 


0.04382 


0. 07844 


0.0 7406 


14 


1.23742 


0.046 39 


0. 10985 


0.09023 


16 


1.31943 


0. 04910 


0. 14 706 


0.10707 


18 


1.40546 


0.05198 


U. 19023 


0.12450 


20 


1.49590 


0.05502 


0.23947 


0. L+249 


22 


1.59113 


0.05825 


0.29491 


0.16100 


24 


1.69152 


0.06166 


0.35667 


0. 17998 


26 


1.79745 


0.06527 


0.42483 


0. 19941 


28 


1.90928 


0.06909 


0.49 951 


0.21927 


30 


2.02 740 


0.0 7314 


0. 56076 


0.23953 


32 


2.15222 


0.07 742 


0.66873 


0.26018 


34 


2.28414 


0.08196 


0.76 345 


0.28119 


36 


2.42362 


0.0 66 76 


0. 86501 


0.30255 


38 


2.57109 


0.09184 


0.97 348 


0.32425 


40 


2.72 706 


0.0 9722 


1.08893 


0.34627 


42 


2.89202 


0. 10291 


1.21144 


0.36860 


44 


3.06652 


0. 10894 


1.34105 


0.39123 


46 


3.25111 


0. 1 1532 


1.47 784 


0.41416 


48 


3.^4640 


0. 1220 7 


1.62166 


0.43 73 6 


50 


3.65300 


0.12923 


1. 77317 


0.46084 


52 


3.87160 


0.13 679 


1.93 182 


0.48459 


54 


4.10289 


0. 14481 


2. 09739 


0.5 0859 


56 


4.34 761 


0.15329 


2.27139 


0.5 32 84 


58 


4.60654 


0.16227 


2.45240 


0.55734 


60 


4.88053 


0.17177 


2. 64095 


0. 5a208 


62 


5.17 045 


0.18183 


2.83 711 


0.60705 


64 


5.47722 


0.192 48 


3.04092 


0.63225 


66 


5.80183 


0.20375 


3.25240 


0.6^76 I 


68 


6. 14 531 


0.2 1569 


3.47162 


0.63331 


70 


6.50877 


0.22832 


3.69 362 


0.70916 


72 


6.89337 


0.24 169 


3. 93343 


0.73 521 


74 


7.30032 


0.2 55 85 


4. 17oll 


0. 7ol46 


76 


7.73095 


0.2 7084 


4.42668 


0.7 8 794 


78 


8. 186 59 


0.28670 


4.68519 


0.8 1460 


80 


8.66875 


0.30349 


4.95168 


0.34145 



241 



Table 53. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for tangent sections with. +4% grade 



VEHICLE 


OPERATION 


PARAMETERS 






SPEED 


FUEL 


OIL 


TIRES 


MA INT 


2 


0.82212 


0.03 2*6 


0.00170 


0.00757 


4 


0.92226 


0.0 3446 


0.00 766 


0.01841 


6 


1.00942 


0.03658 


0.01846 


0.03096 


8 


1.09 3 74 


0.03883 


0.03447 


0.04477 


10 


1.17857 


0.04122 


0.05594 


0.05960 


12 


1.26555 


0.04376 


0.08310 


0.07529 


14 


1.35568 


0.04645 


0. 11611 


0.09175 


16 


1.44967 


0.04932 


0. 15513 


0.10888 


18 


1.54808 


0.05235 


0.20031 


0.12662 


20 


1.65142 


0.05558 


0.25176 


0.14493 


11 


1.76014 


0.05900 


0.30961 


0.16377 


24 


1.37469 


0.06263 


0.37395 


0.18310 


26 


1.99549 


0.06649 


0.44489 


0.20288 


28 


2.12301 


0.07058 


0.52251 


0.22310 


30 


2.2 5 769 


0.07493 


0.60689 


0.24374 


32 


2.39999 


0.0 7954 


0.69813 


0.26476 


34 


2.55042 


0.08444 


0.79 628 


0.26616 


36 


2.70946 


0.06964 


0.90144 


0.3 792 


38 


2.87766 


0.0S*516 


1.01365 


0.3 3 002 


40 


3.05557 


0. 10102 


1. 13299 


0.3 52 45 


42 


3.24379 


0.10724 


1.25953 


0.37520 


44 


3.44294 


0. 11385 


1.39332 


0.39825 


46 


3.65 3 66 


0. 12086 


1.53441 


0.42161 


48 


3.8 7666 


0.12830 


1.68287 


0.44525 


50 


4.11265 


0.13620 


1.83875 


0.46917 


52 


4.36241 


0.14459 


2.00209 


0.49336 


54 


4.62675 . 


0.15350 


2. 17296 


0.51782 


56 


4.90653 


0. 162 95 


2.35 140 


0.54254 


58 


5.20267 


0.172 98 


2.53 745 


0.56750 


60 


5.51611 


0.18 364 


2.73115 


0.59271 


62 


5.84789 


0. 19494 


2.93256 


0.61816 


64 


6.19907 


0.20695 


3. 14173 


0.64384 


66 


6.57078 


0.21969 


3.35 867 


0.6&974 


68 


6.96423 


0.23322 


3.58345 


0.69587 


70 


7.38070 


0.24759 


3.816L0 


0. 72222 


72 


7.82153 


0.26283 


4.05666 


0.74878 


74 


8.28814 


0.27902 


4. 30517 


0.77554 


76 


8.78204 


0.29620 


4. 56166 


0.80252 


78 


9.30481 


0.31444 


4.82617 


0.82969 


80 


9.85816 


0.33380 


5.09 874 


0.35706 



242 



Table 54. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for tangent sections with +5% grade 



VEHICLE OPERATION PARAMETERS 
SPEED FUEL OIL 



TIRFS 



MA I NT 



2 


0.86396 


4 


0.98367 


6 


1.08602 


8 


1.18400 


10 


1.28194 


12 


1.38194 


14 


1.48524 


16 


1.5927b 


18 


1.70518 


20 


1.82311 


11 


1.94710 


24 


2.0 7 768 


26 


2.21536 


28 


2.36067 


30 


2.51413 


32 


2.67629 


34 


2.84772 


36 


3.02901 


38 


3.22077 


40 


3.42 3 66 


42 


3.63835 


44 


3.86556 


46 


4. 10606 


48 


4.36063 


50 


4.63013 


52 


4.91544 


54 


5.21750 


56 


5.53732 


58 


5.87593 


60 


6.23446 


62 


6.61408 


64 


7.01603 


66 


7.441 64 


68 


7.89228 


70 


8.36944 


11 


8.87467 


74 


9.40962 


76 


9.97605 


78 


10.57577 


80 


11.21077 



0.03196 
0.03402 
0.03622 
0.03856 
0.04105 
0.04 3 70 
0.04652 
0.04953 
0.052 73 
0.05613 
0.0 59 76 
0.06362 
06773 
07211 
07677 
08172 
08 700 
0.09262 
0.09361 
0. 10498 
0.11176 
0. 11898 
0.12667 
0. 13435 
0. 14356 
0.15283 
0.16271 
0.17322 
0. 13441 
0.19632 
0.20900 
0.22251 
0.23688 
0.25218 
0.26847 
0.28582 
0.3 0428 
0.32394 
0.34487 
0.36714 



0.00185 
0.00825 
0.01977 
0. 03674 
0.05943 
0. 03803 
0. 122 72 

0. 16364 
0.21092 
0.2b469 
0.32504 
0.39208 
0.46589 
0. 54656 
0.63418 
0. 72881 
0.83053 
0.93 939 
1.05543 

1. 17834 
L. 30954 
1.44702 
1. 59 316 
1. 74ol8 
1.90676 
2.07492 
2.25073 
2.43422 
2.62 544 
2.82443 
3.03123 
3.24588 
3.46343 
3.69889 
3.93733 
4.18375 
4.43823 
4.70077 
4.97141 
5.25013 



0.00 76 8 
0.01870 
0.03l4b 
0.04550 
0.06058 
0.07655 
0.093 29 
0.11072 
0.12878 
0. 1^742 
0.16659 
0.18627 
0. 206^2 
0.22700 
0.24801 
0.26943 
0.2 9122 
0.31338 
0.33589 
0.35874 
0.33191 
0.40540 
0.42919 
0.45328 
0.47765 
0.50230 
0.52 722 
0.55240 
0.57784 
0.60353 
0.62946 
0.65563 
0.63203 
0.7086b 
0.73552 
0.76259 
0.7H987 
0.81736 
0.84506 
0.87296 



2 43 



Table 55. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for tangent sections with +6% grade 



VEHICLE OPERATION PARAMETERS 
SPEED FUEL OIL 



TIRES 



MA I NT 



2 


0.90792 


4 


1.04917 


6 


1.16843 


8 


1.28172 


10 


1.39438 


12 


1.50 902 


14 


1.62719 


16 


1. 74997 


18 


1.87822 


20 


2.01265 


11 


2. 15392 


24 


2.30265 


26 


2.45945 


28 


2.62493 


30 


2.799 70 


32 


2.98440 


34 


3.17969 


36 


3.38625 


38 


3.60479 


40 


3.8360a 


42 


4.08089 


44 


4.34006 


46 


4.61446 


48 


4.90503 


50 


5.21272 


52 


5.53858 


54 


5.88369 


56 


6.24920 


58 


6.63632 


60 


7.04636 


62 


7.48066 


64 


7.94068 


66 


8.42792 


68 


8.94399 


70 


9.49062 


11 


10.06961 


74 


10.68285 


76 


11.33239 


78 


12.02032 


80 


12.74897 



0.03146 
0.03 3 59 
0.03586 
0.0 38 29 
0.04088 
0.04364 
0.04659 
0.049 74 
0.053L1 
0.0 56 70 
0.06053 
0.0o463 
0.06900 
0. 7366 
G. 07865 
0.08396 
0.08964 
095 71 
L0218 
10909 

1 1647 
0.12434 
0. 13275 
0.14L73 
0.15131 
0.16155 
0.17247 
0. 18414 
0. 19659 
0.20988 

22408 
23923 
25541 

2 7268 
29113 

0.31081 
0.33183 
0.35428 
0. 37823 
0.40381 



0.00 202 
0.0Q8S9 
0.02116 
0. 03916 
0.06314 
0.09 32 7 
0. 12971 
0. 17262 
0.22210 
0.27828 
0.34124 
0.41108 
0.48789 
0.57173 
0.66270 
0. 76 084 
0.86624 
0.97 895 
1.09 903 
i. 22654 
1. 36153 
1. 50405 
1.65415 
1.81 188 
1.97729 
2. 15041 
2.33129 
2. 51998 
2. 71651 
2.92 091 
3. 13 32 3 
3.35351 
3.581 73 
3. 81806 
4.06242 
4.31485 
4.57541 
4. 84413 
5.12102 
5.40614 



0.00 780 
0.01899 
0.03196 
0.04624 
0.0ol5b 
0.07782 
0.09485 
0.11259 
0.13097 
0. 14995 
0.16947 
0.18950 
0.21001 
0.23097 
0.25237 
0.27417 
0.2V63 7 
0.31894 
0.34166 
0.3o514 
0.38874 
0.41267 
0.43691 
0.46145 
0.48626 
51140 
53679 
56245 
5 883 7 
0.61455 
0.64098 
0.66 76 5 
0.69455 
0.72169 
0.74906 
0. 7 76 65 
0.80446 
0.83243 
0.66072 
0.38916 



244 



Taole 56. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for tangent sections with. -1% grade 



VEHICLE 


OPERATION 


PARAMETERS 






SPEED 


FUEL 


OIL 


TIRES 


MAINT 


2 


0.55249 


0.03401 


0.00141 


0.00729 


4 


0.49751 


0.03580 


0.00631 


0.017 54 


6 


0.45249 


0.03 768 


0.01515 


0.02932 


8 


0.41494 


0.03966 


0.02820 


0.04222 


10 


0.38314 


0.04174 


0.04567 


6.05602 


12 


0.40392 


0.04394 


0.06770 


0.07057 


14 


0.43115 


0.04625 


0.09445 


0.08579 


16 


0.4t>430 


0.04368 


0. 12603 


0. 10161 


18 


0.50305 


0.05124 


0. 16254 


0.11796 


20 


0.54716 


0.05393 


0.20408 


0. 13481 


21 


0.59651 


0.05677 


0.25 074 - 


0. 15211 


24 


0.65107 


0.05975 


0.30258 


0. 16984 


26 


0.71084 


0.06290 


0.35969 


0.13797 


28 


0.77588 


0.06620 


0.42213 


0.20647 


30 


0.84630 


0.06968 


0.48997 


0.22 53 3 


32 


0.92225 


0.07335 


0.56326 


0.24453 


34 


1.00390 


0.07720 


0.64207 


0.26405 


36 


1.09147 


0.08126 


0. 72644 


0.23389 


38 


1. 18519 


0.08553 


0.81643 


0.30401 


40 


1.28533 


0.09003 


0.91208 


0.32443 


42 


1.39218 


0.09476 


1.01345 


0.34512 


44 


1.50607 


0.09975 


1.12058 


0.36607 


46 


1.62734 


0.10499 


1.23351 


0.38728 


43 


1.75637 


0.11051 


1.35228 


0.40873 


50 


1.89358 


0. 116 32 


1.47693 


0.43043 


52 


2.03938 


0. 12244 


1.60 750 


0.45236 


54 


2.19425 


0.12887 


1. 74403 


0.47452 


56 


2.35869 


0. 13565 


1. 88656 


0.49639 


58 


2.53321 


0. 1427b 


2.03512 


0.51948 


60 


2.71838 


0.15029 


2.18973 


0.54228 


62 


2.91481 


0. 156 19 


2. 35045 


0.56529 


64 


3.12313 


0. 16651 


2.51 729 


0.58849 


66 


3.34401 


0.17526 


2.69029 


0.61189 


68 


3.5 7817 


0.18 448 


2.86 943 


0.63547 


70 


3.8263b 


0.19417 


3.05490 


0.65925 


72 


4.03 940 


0.20438 


3.24655 


0.68320 


74 


4.36814 


0.21513 


3.44449 


0. 70733 


76 


4.66349 


0.2 2 644 


3.64873 


0.7^164 


78 


4.97641 


0.23834 


3.85930 


0. 7 56 L 2 


80 


5.30792 


0.25088 


4.07623 


0.78077 



245 



Table 57. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for tangent sections with -2% grade 



VEHICLE 


OPERATION 


PARAMETERS 






SPEED 


FUEL 


OIL 


TIRES 


MA I NT 


2 


0.55249 


0.03348 


0.00164 


0.00744 


4 


0.49751 


0.03534 


0.00699 


0.01778 


6 


0.45249 


0.0 3 731 


0.01632 


0.02958 


8 


0.41494 


0.03938 


0.02978 


0.04246 


10 


0.38314 


0.04157 


0.04747 


0.05619 


12 


0.35587 


0.04388 


0.06949 


0.07065 


14 


0.33223 


0.04632 


0.09591 


0.03575 


16 


0.31153 


0.04889 


0.12678 


0.10141 


18 


0.32217 


0.05161 


0. 16217 


0.11757 


20 


0.36628 


0.05448 


0.20211 


0.13421 


22 


0.41563 


0.05 750 


0.246b7 


0.15128 


24 


0.47019 


0.06070 


0.29586 


0.16875 


26 


0.52996 


0.06407 


0.34973 


0.13659 


28 


0.59500 


0.06763 


0.40832 


0.20479 


30 


0.66542 


0.0 7139 


0.47166 


0.22333 


32 


0.74137 


0.07536 


0.53977 


0.24219 


34 


0.82303 


0.07954 


0.61268 


0.26135 


36 


0.91059 


0.08396 


0.69043 


0.28080 


38 


1.00431 


0.08863 


0.77302 


0.30053 


40 


1.10445 


0.09356 


0. 86050 


0.32053 


42 


1.21130 


0.09875 


0.95287 


0.34079 


44 


1.32519 


0. 10424 


1.05017 


0.36130 


46 


1.44 646 


0. 11003 


i. 15241 


0.3 82 04 


48 


1.57550 


0.11615 


1.25962 


0.40302 


50 


1.71270 


0. 12260 


1.37180 


0.42422 


52 


1.85851 


0. 129 42 


1.48899 


0.44 5 64 


54 


2.01337 


0. 13661 


1.61119 


0.46727 


56 


2.17781 


0. 14420 


1. 7:>8<*3 


0.48911 


58 


2.35233 


0. 15221 


1.87072 


0.51115 


60 


2.53 751 


0. 16067 


2.00807 


0.53339 


62 


2.73394 


0.16960 


2. 15052 


0.55581 


b4 


2.9^225 


0. 17902 


2.29805 


0.57843 


66 


3. 16 313 


0. 188V7 


2.45070 


0.60122 


68 


3.39729 


0.19947 


2.60848 


0.62419 


70 


3.64548 


0.21056 


2.77140 


0. 6473 3 


12 


3.90852 


0.22226 


2.93947 


0.6 7065 


74 


4.18 727 


U. 2 3 461 


3.11270 


0.69413 


76 


4.48262 


0.24 764 


3.29113 


0.71777 


78 


4.79554 


0.26141 


3.47V73 


0. 74158 


80 


5. 12704 


0.27593 


3.66355 


0. 75554 



246 



Table 58- Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 

for tangent aecttons wAth. -3% grade 



VEHICLE OPERATION PARAMETERS 
SPEED FUEL OIL 



TIKES 



MAI NT 



2 


0.55249 


0.03297 


0.00191 


0.00760 


4 


0.49751, 


0.034 90 


0.00775 


0.0L801 


6 


0.45249 


0.U3694 


0.01759 


0.02984 


8 


0.41494 


0. 03910 


0.03144 


0.042 70 


10 


0.38 314 


0.04139 


C. 04935 


0.05637 


12 


0.35587 


0.04382 


0.07133 


0.07074 


14 


0.33223 


0.04639 


0.09T38 


0.08570 


16 


0.31153 


0.04910 


0. 12753 


0.10120 


18 


0.2932c 


0.05198 


0. 16179 


0.11719 


20 


0.27701 


0.0 5502 


0.20016 


0.13361 


22 


0.26247 


0.05825 


0.24256 


0.15045 


24 


0.24938 


0.06166 


0.28929 


0.16766 


26 


0.30914 


0.0o527 


0. 34006 


0.18523 


28 


0.37419 


0.0o909 


0.39497 


0.20313 


30 


0.44461 


0.0 73 14 


0.45403 


0.22135 


32 


0.52056 


0.07 742 


0.51726 


0.23987 


34 


0.60221 


0.08196 


0. 58464 


0.25668 


36 


0.68978 


0.08676 


0.65620 


0.2/775 


38 


0. 78350 


0.09184 


0.73192 


0.29709 


40 


0.8 8364 


0.09722 


0.81183 


0.31669 


42 


0.99049 


0.10291 


0.89591 


0.33652 


44 


1.10438 


0.10894 


0.98-+19 


0.35658 


46 


1.22565 


0. 11532 


1.07665 


0.37687 


48 


1.35468 


0. t2207 


1. 17 330 


0.3 973 8 


50 


1.49189 


0.12923 


1.27416 


0.41ol0 


52 


1.63769 


0. 13679 


1.37921 


0.43902 


54 


1.792 5b 


0. 14481 


1.48847 


0.46014 


56 


1.95 699 


0.15329 


1.60193 


0.48146 


58 


2. 13152 


0. 16227 


1. 71960 


0.5 02 96 


60 


2.31669 


0. 17177 


1.84149 


0.52464 


62 


2.51312 


0.18183 


1.96 759 


0.54650 


64 


2.72144 


0. 19248 


2.09791 


0.56854 


66 


2.94232 


0.20375 


2.23245 


0.59074 


68 


3.17648 


0.21569 


2.37122 


0.61311 


70 


3.42467 


0.22832 


2.51^t21 


0.6356^ 


72 


3.68771 


0.24169 


2.66143 


0.65833 


74 


3.96645 


0.25585 


2.81288 


0.68117 


76 


4.26180 


0.27084 


2. 96 85 7 


0. 70417 


78 


4.57472 


0.28670 


3.12 849 


0. 72731 


80 


4.90623 


0.30349 


3.29265 


0.75060 



247 



Table 59. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for tangent sections with -4% grade 



VFHlCLb 


OPERATION 


PARAMETERS 






SPEED 


FUEL 


UIL 


TIRES 


MA I NT 


2 


0.55249 


. 3 2 46 


0.00222 


0.00 776 


4 


0.49751 


0.03446 


0.00359 


0.01826 


6 


0.45249 


0.03658 


0.01895 


0.03011 


8 


0.41494 


0.03883 


0.03320 


0.04294 


10 


0.38314 


0.04122 


0. 05131 


0.05655 


12 


0.35 587 


0.043 76 


0.07321 


0.0/002 


14 


0.33223 


0.04645 


0.09888 


0.08566 


16 


0.31153 


0. 04932 


0. 12829 


0.10100 


18 


0.29326 


0.05235 


0. 16141 


0.1 1680 


20 


0.27701 


0.05558 


0.19823 


0.13 30? 


22 


0.2b247 


0.05900 


0.23872 


0.14962 


24 


0.24938 


0.0o263 


0.28286 


0.16658 


26 


0.23753 


0.06649 


0.3 3 064 


0.18387 


28 


0.22676 


0.07058 


0.38205 


0.20148 


30 


0.21692 


0.0749 3 


0.43707 


0.21939 


32 


0.25099 


0.07954 


0.495e>8 


0.23757 


34 


0.33264 


0.08444 


0.55 789 


0.2 5603 


36 


0.42021 


O.Cd964 


0.62 3o7 


0.27474 


38 


0.51393 


0. 09516 


0.69301 


0.29369 


40 


0.61407 


0. 10102 


0. 76591 


0.31263 


42 


0.72092 


0. 10724 


0. 84236 


0.33230 


44 


0.83481 


0.11385 


0.92 235 


0.3 5193 


46 


0.95608 


0. 12 086 


1.00586 


0.3 7178 


48 


1.08 512 


0.12830 


1. 09290 


0.39182 


50 


1.22232 


0.1 3620 


1. 18346 


0.41207 


52 


1.36812 


0.1Vt59 


1.27 /52 


0.43250 


54 


1.52299 


0. 153 50 


1.37508 


0.45312 


56 


1.68743 


0.16295 


1.47614 


0.47392 


58 


1.86195 


0.17298 


1. 58069 


0.49489 


60 


2.04713 


0. 18364 


1.68871 


0.51603 


62 


2.24355 


0. 19494 


1.80022 


0.53734 


b<* 


2.45167 


0.2 0695 


1.91519 


0.55881 


66 


2.67275 


0.21969 


2.03 3 63 


0.58044 


68 


2.90691 


0.23322 


2. 15553 


0.60222 


70 


3.15510 


0.24 759 


2.28088 


0.62415 


72 


3.41814 


0.2628 3 


2.409o6 


0.64623 


74 


3.69689 


0.27902 


2.54192 


0.66645 


76 


3.99223 


0.29620 


2.67761 


0.69082 


78 


4.30515 


0.31444 


2.81673 


0.71332 


80 


4.63666 


0.33380 


2.95928 


0.73596 



248 



Table 60. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for tangent sections witk -S% grade 



VEHICLE 


OPERATION 


PARAMETERS 






SPEED 


FUEL 


OIL 


TIRES 


MAINT 


2 


0.55249 


0.03196 


0.00259 


0.00792 


4 


0.49751 


0.03402 


0. 00953 


0.01850 


6 


0.45249 


0.03622 


0.02041 


0.03 037 


8 


0.41494 


0.0 3 856 


0.03506 


0.04318 


10 


0.38314 


0.04105 


0.05334 


' 0.05673 


12 


0.35587 


0.043 70 


0.07514 


0.07090 


14 


0.33 223 


0.04652 


0. 10040 


0.08561 


16 


0.31153 


0.049 53 


0. 12905 


0.10030 


18 


0.29326 


0.05273 


0.16104 


0.116 42 


20 


0.27701 


0.05613 


0. 19632 


0.13243 


22 


0.26247 


0.05976 


0.23484 


0.148 80 


24 


0.24938 


0.06362 


0.27658 


0.16551 


2b 


0.23753 


0.06773 


0. 32149 


0.18253 


28 


0.22676 


0.0/211 


0. 36955 


0. 19984 


30 


0.21692 


0.07677 


0.42074 


0.21744 


32 


0.20790 


0.08172 


0.47501 


0.23530 


34 


0. 19 960 


0.08700 


0. 53236 


0.2 5341 


36 


0.19194 


0.09262 


0.59275 


0.27175 


38 


0. 18484 


0.09861 


0.65617 


0.29033 


40 


0.28498 


0. 10498 


0. 72259 


0.30913 


42 


0.39183 


0.11176 


0.79201 


0.32813 


44 


0.50572 


0. 11898 


0. 86439 


0.34 734 


46 


0.62700 


0. 126b7 


0.93973 


0.36675 


48 


0. 75603 


0. 13485 


1.01801 


0.38635 


50 


0.89323 


0. 14356 


1.09922 


0.40612 


52 


1.03 904 


0. 152 83 


I. 18 33 3 


0.42.O06 


54 


1. 19391 


0.16271 


1.27034 


0.44621 


56 


1.35834 


0.17322 


1.36024 


0.46650 


58 


1.53287 


0. I84fl 


1.45 300 


0.4d6 9fc 


60 


1. 71804 


0. 19632 


1.54862 


0.50757 


62 


1.91447 


0.20900 


1.64 709 


0. 52634 


64 


2.12278 


0.22251 


1.74839 


0.54926 


66 


2.34366 


0.23688 


1.85252 


0.57032 


68 


2.57782 


0.252 18 


1. 95 94o 


0.59153 


70 


2.82601 


0.26 84 7 


2.06921 


0.61288 


12 


3.03906 


0. 28 5 82 


2. 18175 


0.63436 


74 


3.36760 


0.30428 


2.2 9 708 


0.65i>93 


76 


3.66315 


0.323 94 


2.41518 


0.67773 


78 


3.9/607 


0. '344 87 


2.53605 


0.6 996 


80 


4.30757 


0.36714 


2.65968 


0. 72160 



249 



Table 61. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for tangent sections with. -6% grade 



VEHICLE 


OPERATION 


PARAMETERS 






SPEED 


FUEL . 


OIL 


TIRES 


MA I NT 


2 


0.55249 


0.03146 


0.00301 


0.00809 


4 


0.49751 


0.03359 


0.01056 


0.01875 


6 


0.45249 


0.03586 


0.02200 


0.03064 


8 


0.41494 


0.03829 


0.03 702 


0.04343 


10 


0.38314 


0.04088 


0.05545 


0.05691 


12 


0.35587 


0.04364 


0.07713 


0.07098 


14 


0.33223 


0.04659 


0.10195 


0.08557 


16 


0.311.53 


0.049 74 


0. 12982 


0.10060 


18 


0.293 26 


0.05311 


0. 16067 


0.11603 


20 


0.27701 


0.05670 


0.19442 


0.13184 


22 


0.26247 


0.06053 


0.23103 


0.14798 


24 


0.24938 


0.064o3 


0.27043 


0.16444 


26 


0.23753 


0.06900 


0.31259 


0.18119 


26 


0.22676 


0.07366 


0.35747 


0.19822 


30 


0.21692 


0.0/865 


0.40501 


0.21551 


32 


0.20790 


0.03396 


0.45520 


0.23304 


34 


0.19960 


0.08964 


0.50799 


0.25081 


36 


0.19194 


0.09571 


0.56336 


0.26880 


38 


0. 18484 


0. 10218 


0.62128 


0.28701 


40 


0.17825 


0. 10909 


0.68172 


0.30542 


42 


0.17212 


0.11647 


0.74466 


0.32402 


44 


0.16639 


0. 12434 


0.81008 


0.34282 


46 


0.22525 


0. 132 75 


0.87795 


0.3 6179 


48 


0.35428 


0.14173 


0.94826 


0.38094 


50 


0.49149 


0. 15131 


1.02098 


0.40026 


52 


0.63729 


0. 16155 


1.09609 


0.41975 


54 


0.79216 


0.17247 


1. 17358 


0.4 3940 


56 


0.95659 


0. 18414 


1.25343 


0.45920 


58 


1. 13112 


0.19659 


1.33562 


0.47915 


60 


i. 31629 


0.20988 


1.42 015 


0.4992 5 


62 


1.51272 


0.22408 


1.50699 


0.51949 


64 


1.72104 


0.23923 


1.59612 


0.53987 


66 


1.94192 


0.25541 


1.68754 


0.56038 


68 


2.17607 


0.27268 


1.78123 


0.58103 


70 


2.42427 


0.29113 


1.87719 


0.60180 


12 


2.68 731 


0.31081 


1.97536 


0.62271 


74 


2.96605 


0.33 183 


2.07582 


0.64373 


76 


3.26140 


0.35428 


2.17848 


0.66488 


78 


3.5 7432 


0.37H23 


2.28334 


0.68614 


80 


3.90582 


0.40361 


2.39041 


0.70752 



250 



Table 62. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for level sections with 1° curvature 



VEHICLE OPERATION PARAMETERS 
SPEED FUEL OIL 



TIRES 



MA INT 



2 


0.6546.3 


0.03454 


0.05279 


0.007L4 


4 


0.69464 


0.03625 


0. 06187 


0.01731 


6 


0.73709 


0.03805 


0.07250 


0.02907 


8 


0.78213 


0. 03994 


0.08496 


0.04198 


10 


0.82993 


0.04192 


0.09956 


0.05584 


12 


0.88065 


0.04400 


0. 11667 


0.0 7049 


14 


0.93447 


0.046 18 


0. 13672 


0.08584 


16 


0.99158 


0.048^7 


0.16022 


0.10181 


18 


1.05217 


0.05087 


0. 18 776 


0.1 163 5 


20 


1.11647 


0.05340 


0.22003 


0.13541 


22 


1.18470 


0.05605 


0.25784 


0.15295 


24 


1.25710 


0.05882 


0. 30216 


0.17094 


26 


1.33393 


0.06174 


0.35409 


0.18935 


28 


1.41545 


0.06480 


0.41495 


0.20816 


'30 


1.50195 


0.06802 


0.48626 


0.22735 


32 


1.59 3 73 


0.07139 


0. 56984 


0.24690 


34 


1.69113 


0.07493 


0.66778 


0.26O79 


36 


1.79448 


0.07865 


0. 78255 


0.28700 


38 


1.90414 


0.08255 


0.91704 


0.30754 


40 


2.02051 


0.08664 


1.07465 


0.32837 


42 


2.14398 


0.09094 


1.25 93 5 


0.3t950 


44 


2.27501 


0.09545 


1.47580 


0.37091 


46 


2.41404 


0.10018 


1. 72944 


0.39259 


48 


2.56156 


0.10515 


2.02668 


0.41453 


50 


2.71811 


0. 11036 


2.37500 


0.43673 


52 


2.88421 


0. 11583 


2.78319 


0.45918 


54 


3.06047 


0. 12158 


3.26153 


0.48187 


56 


3.24751 


0. 12761 


3.82209 


0.50480 


58 


3.44 597 


0.13394 


4.47898 


0.52795 


60 


3.65656 


0.14058 


5.24878 


0.55133 


62 


3.88002 


0.14755 


6. 15088 


0.57492 


64 


4.11713 


0.15487 


7.20803 


0.59d73 


66 


4.36874 


0. 16254 


8.44687 


0.62274 


68 


4.63572 


0.17061 


9.89862 


0.64696 


70 


4.91902 


0.17907 


11.59989 


0.67138 


11 


5.21963 


0.18795 


13.59355 


0.69599 


74 


5.53862 


0.19727 


15.92986 


0.72079 


76 


5.87709 


0.20 705 


18.66769 


0.74578 


78 


6.23625 


0.21732 


21. 87608 


0.7 7095 


80 


6.61736 


0.22809 


25.63 591 


0.79631 



2 51 



Table S3. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for level sections with 2° curvature 



VEHICLE 


OPERATION 


PARAMETERS 






SPEED 


FUEL 


OIL 


TIRES 


MA I NT 


2 


0.65220 


0.03454 


0. 07 983 


0.00 714 


4 


0.69 046 


0.03625 


0.09398 


0.01731 


6 


0. 73096 


0.03305 


0. 11064 


0.02907 


8 


0.77383 


0.03994 


0. 13026 


0.04198 


10 


0.81922 


0.0^-192 


0. 15335 


0.05584 


12 


0.86727 


0.044U0 


0. 18053 


0.07049 


14 


0.9L814 


0.04c 1.8 


0.2125<* 


0.03584 


16 


0.9 7 200 


0.04 84 7 


0.25021 


0.10131 


18 


1.02901 


0.0508/ 


0.29457 


0.11835 


20 


1.08 93 7 


0.05340 


0.34679 


0.13541 


11 


1.15327 


0.05605 


0.40626 


0.15295 


24 


1.2 2 204 


0.05882 


0.48064 


0. 17094 


26 


1.30019 


0.06 174 


0.5b 5 84 


0. 18935 


28 


1.33333 


0.06^80 


0.66615 


0.2081b 


30 


1.47179 


0-06802 


0.76 424 


0.22735 


32 


1.56591 


0.0 7139 


0.92326 


0.2^-690 


3 4 


1.66604 


0.07493 


I .06693 


0.26679 


36 


1. 77258 


0.0 7865 


1.27961 


0.26700 


38 


1.88593 


0.08255 


1. 50645 


0.30 754 


40 


2.00654 


0.08664 


1.77350 


0.32837 


42 


2.134S5 


0.09094 


2.06 789 


0.3495U 


44 


2.27136 


0. 09545 


2.45802 


0.37091 


46 


2.41661 


0. 1001b 


2.89376 


0.3 92 59 


48 


2.57115 


0.10515 


3.40674 


0.41453 


50 


2. 73 556 


0.11036 


4.01066 


0.43673 


52 


2.91049 


0.11533 


4.72164 


0.45918 


54 


3.09661 


0.121 58 


5.55865 


0.46 187 


56 


3.29463 


0.12 761 


6. 5^h04 


0.50460 


58 


3.50531 


0. 133 94 


7. 70411 


0.52 795 


60 


3.72947 


0. 14058 


9.06984 


0.55133 


62 


3.96 795 


0. L4755 


10.67767 


0.5 7492 


64 


4.22169 


0.15487 


12.57 053 


0.59873 


66 


4.49166 


0. 16254 


14.79692 


0.62274 


68 


4. 77889 


0. 170bl 


17.42 23 5 


0.64696 


70 


5.08449 


0.17907 


20.51083 


0.67138 


72 


5.40962 


0. 18795 


24. 14665 


0.69599 


74 


5. 75556 


0.19/27 


28.42 740 


0.72079 


76 


6. 12360 


0.20705 


33.46680 


0. 7^578 


7b 


6. 51519 


0.21732 


39.39951 


0.77095 


80 


6.93182 


0.22809 


46.38396 


0.79631 



252 



Table .64. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for level sections with 3° curvature 



VEHICLE 


OPERATION 


PARAMETERS 






SPEED 


FUEL 


OIL 


TIRES 


MAINT 


2 


0.65220 


0.03454 


0.10167 


0.00714 


4 


0.69046 


0.03625 


0. 12049 


0.01731 


6 


0.73096 


0.03805 


0. 14250 


0.02907 


8 


0.77383 


0.03994 


0. 16853 


0.04198 


10 


0.81922 


0.04192 


0.19932 


0.05584 


12 


0.86727 


0.044 00 


0.23574 


0.07049 


14 


0.91814 


0.04618 


0.27881 


0.08584 


16 


0.97200 


0.04847 


0.32975 


0.10181 


18 


1.02901 


0.05087 


0.39 000 


0.11835 


20 


1.08937 


0.05340 


0.46125 


0.13541 


22 


1.15327 


0.05605 


0.54552 


0.15295 


24 


1.22091 


0.05882 


0.64518 


0.17094 


26 


1.30145 


0.06174 


0.76306 


0.18935 


28 


1.38854 


0.06480 


0.90247 


0.20816 


30 


1.48146 


0.06802 


1.06735 


0.22735 


32 


1.58060 


0.0 7139 


1.26235 


0.24690 


34 


1.68637 


0.07493 


1.49293 


0.26679 


36 


1.79 921 


0.0 7865 


1.76575 


0.28700 


38 


1.91961 


0.08255 


2.08836 


0.30754 


40 


2.04807 


0.08664 


2.46990 


0.32837 


42 


2.L8512 


0.09094 


2.92115 


0.34950 


44 


2.33L35 


0.09545 


3.45484 


0.37091 


46 


2.48736 


0.10018 


4.08605 


0.39259 


48 


2.65380 


0.10515 


4.83257 


0.41453 


50 


2.83139 


0. 11036 


5.71547 


0.43673 


52 


3.02086 


0. 11583 


6.75 968 


0.45918 


54 


3.22301 


0.12158 


7.99466 


0.48187 


56 


3.43868 


0.12761 


9.45531 


0.50480 


58 


3.66880 


0. 13394 


11. 18279 


0.52795 


60 


3.91430 


0. 14058 


13.22589 


0.55133 


62 


4.17624 


0. 14755 


15.64226 


0.5 7492 


64 


4.45570 


0. 15487 


18.50009 


0.59873 


66 


4.75387 


0. 162 54 


21.88004 


0.622/4 


68 


5.07199 


0. 17061 


25.87752 


0.64696 


70 


5 . 4 1 1 40 


0. 17907 


30.60535 


0.67138 


72 


5.77351 


0.18795 


36. 19695 


0.69599 


74 


6.15986 


0.19727 


42.81012 


0.72079 


76 


6.57207 


0.20705 


50.63153 


0.745 78 


78 


7.01 185 


0.2173? 


59.88191 


0.77095 


80 


7.48108 


0.22809 


70.82 234 


0.79631 



253 



Table 65. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for level sections with 4 curvature 



VEHICLE 


OPERATION 


PARAMETERS 






SPEED 


FUEL 


OIL 


TIRES 


MA I NT 


2 


0.65220 


0.03454 


0.12128 


0.00714 


4 


0.69046 


0.03625 


0.14409 


0.01731 


6 


0.73096 


0.03805 


0.17121 


0.02907 


8 


0.77383 


0.03994 


0.20342 


0.04198 


10 


0.81922 


0.04192 


0.24169 


0.05584 


12 


0.86727 


0.04400 


0.28 717 


0.07049 


14 


0.91814 


0.04618 


0.34120 


0.08584 


16 


0.97200 


0.04847 


0.40 540 


0.10181 


18 


1.02901 


0.05087 


0.48167 


0.11835 


20 


1.08937 


0.05340 


0.57230 


0. 13541 


22 


1.15 327 


0.05605 


0.67998 


0.15295 


24 


1.23201 


0.05882 


0.8 792 


0.17094 


26 


1.31828 


0.06174 


0.95994 


0.18935 


28 


1.41061 


0.06480 


1.14055 


0.2U816 


30 


1.50939 


0.06802 


1.35515 


0.22735 


32 


1.61510 


0.07139 


1.61013 


0.24690 


34 


1.72820 


0.07493 


1.91307 


0.26679 


36 


1.84923 


0.07865 


2.27302 


0.28700 


38 


1.97873 


0.08255 


2. 70070 


0.30754 


40 


2.11 731 


0.08664 


3.20885 


0.32837 


42 


2.26558 


0.09094 


3.81260 


0.34950 


44 


2.42424 


0.09545 


4.52995 


0.37091 


46 


2.59402 


0. 10018 


5.38228 


0.39259 


48 


2.77568 


0.10515 


6.39497 


0.41453 


50 


2.97006 


0.11036 


7.59820 


0.43673 


52 


3.17 805 


0.11583 


9.02 782 


0.45918 


54 


3.40062 


0.12158 


10.72643 


0.48187 


56 


3.63 8 77 


0.12761 


12.74464 


0.50480 


58 


3.89 3 59 


0. 13394 


15. 14257 


0.52795 


60 


<♦. lo627 


0.14058 


17.99168 


0.55133 


62 


4.45804 


0. 14755 


21.37688 


0.57492 


64 


4.77024 


0.15487 


2 5.39 900 


0.59873 


66 


5. 10430 


0. 16254 


3 0. 17 790 


0.62274 


68 


5.46176 


0. 17061 


35.85594 


0.64696 


70 


5.84425 


0. 179U7 


42.60237 


0.67138 


72 


6.25 3 53 


0. 18 795 


50.61812 


0.69599 


74 


6.69147 


0.19727 


60. 14203 


0.72079 


76 


7.16008 


0.20705 


71.45798 


0.745 78 


78 


7.66152 


0.21732 . 


84.90297 


0.7 7095 


80 


8. 19805 


0.22 8 09 


100.87776 


0.796 31 



254 



Table 66. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for level sections with 5° curvature 



VEHICLE OPERATION PARAMETERS 

SPEED FUEL OIL TIRES MAINT 



2 


0.6522P 


0.03454 


0. 13898 


0.00714 


4 


0.69046 


0.03625 


0.16589 


0.01731 


6 


0.73096 


0.03805 


0. 19801 


0.02907 


8 


0.77383 


0.03994 


0.23635 


0.04198 


10 


0.81922 


0.04192 


0.28212 


0.05584 


12 


0.86727 


0.04400 


0.33674 


0.07049 


14 


0.9181^ 


0.04618 


0.40195 


0.08584 


16 


0.97200 


0.04847 


0.47 978 


0. 10181 


18 


1.02901 


0.05087 


0.57263 


0.11835 


20 


1.08937 


0.053 40 


0.68357 


0.13541 


11 


1. 16 770 


0.05605 


0.81592 


0.15295 


24 


1.25328 


0.05882 


0.97391 


0.17094 


lb 


1.34514 


0.06174 


1. 16249 


0.18935 


28 


1.44373 . 


0.06480 


1.38759 


0.20816 


30 


1.54955 


0.06802 


1.65 627 


0.22735 


32 


1.66312 


0.07139 


1.97697 


0.24690 


34 


1.78502 


0.07^93 


2.35977 


0.26679 


36 


1.91585 


0.07865 


2.81670 


0.2 8 700 


38 


2.05627 


0.08255 


3.36210 


0.30754 


40 


2.20698 


0.08664 


4.01310 


0.32837 


42 


2.36874 


0.09094 


4.79016 


0.34950 


44 


2.54236 


0.09545 


5.71769 


0.37091 


46 


2.72869 


0.10018 


6.82 481 


0.39259 


48 


2.92869 


0.10515 


8. 14o31 


0.41453 


50 


3.14334 


0.11036 


9.72368 


0.43673 


52 


3.373 73 


0. 11583 


11.60648 


0.45918 


54 


3.62101 


0.12158 


13.85386 


0.48187 


56 


3.88640 


0.12761 


16.53638 


0.50480 


58 


4.17125 


0.13394 


19. 73833 


0.52795 


60 


4.47698 


0. 1^058 


23.56029 


0.55133 


62 


4.80512 


0. 14755 


28. 12230 


0.5749? 


64 


5.15 730 


0.15487 


33.56764 


0.59873 


66 


5.53531 


0. 16254 


40.06735 


0.62274 


68 


5.94101 


0.17061 


47. 82 564 


0.64696 


70 


6.37645 


0.17907 


57.08618 


0.67138 


11 


6.84380 


0.18795 


68.13985 


0.69599 


74 


7.34542 


0.19727 


81.33377 


0.72079 


76 


7.88379 


0.20705 


97.08252 


0.74578 


78 


8.46162 


0.21732 


115.88072 


0.77095 


80 


9.08180 


0.22809 


138.31385 


0.79631 



255 



Table 67. Fuel, tires, oil and maintenance 
in gallons, .001 inches, quarts and 
dollars respectively per vehicle hour 
for level sections with 6° curvature 



VEHICLE 


OPERATION 


PARAMETERS 






SPEED 


FUEL 


OIL 


TIRES 


MA i N T 


2 


0.65220 


0.03454 


0.15548 


0.00714 


4 


0.69 046 


0.03625 


0. 18644 


0.01731 


6 


0.73096 


0.0 3805 


0.22356 


0.02907 


8 


0.77383 


0.03994 


0.26808 


0.04198 


10 


0.8L922 


0.04192 


0.32147 


0.05584 


12 


0.86727 


0.04400 


0.38548 


0.07049 


14 


0.91814 


0.04618 


0.46224 


0.08584 


16 


0.97200 


0.04847 


0.55429 


0.10181 


18 


1.02 901 


0.05087 


0.66467 


0.11835 


20 


1.10546 


0.05340 


0.79703 


0. 13541 


Z2 


1.19026 


0.05605 


0.95574 


0.15295 


24 


1.28L57 


0.05882 


1. 14607 


0.17094 


26 


1.37989 


0.06174 


1.37429 


0.18935 


28 


i. 48574 


0.06480 


1.64795 


0.20816 


30 


1.59972 


0.06802 


1.97612 


0.22735 


32 


1.72 2V* 


0.07139 


2. 36963 


0.24690 


34 


1.35457 


0.07493 


2.84151 


0.26679 


36 


1.99685 


0.07865 


3.40735 


0.28700 


3 8 


2.15004 


0.08255 


4.08587 


0.30754 


40 


2.31497 


0.08664 


4.89 951 


0.32637 


42 


2.49257 


0.09094 


5.87517 


0.3 4950 


44 


2*68378 


0.09543 


7.04511 


0.37091 


46 


2.88967 


0.10018 


8.44804 


0.39259 


48 


3.11135 


0.10515 


10. 13034 


0.41453 


30 


3.35003 


0.11036 


12. 14 763 


0.43673 


52 


3.60702 


0.11583 


14.56664 


0.45918 


34 


3.88373 


0.12158 


17.46733 


0.48187 


56 


4.18167 


0.12761 


20.94569 


0.50480 


58 


4.50247 


0.13394 


25. 11670 


0.52795 


60 


4.84787 


0. 14058 


30.11829 


0.55133 


62 


5.21977 


0. 14755 


36. 11588 


0.57492 


64 


5.62020 


0.15487 


43. '40 782 


0.59873 


66 


6.05135 


0. 16254 


51.9318 7 


0.62274 


68 


6.51558 


0.17061 


62.27328 


0.64696 


70 


7.01542 


0.17907 


74.67401 


0.67138 


72 


7.55360 


0.18795 


89.54424 


0.69599 


74 


8.13307 


0.19727 


107.37553 


0.72079 


76 


8.75700 


0.20705 


12 8.75 764 


0.74578 


78 


9.42878 


0.21732 


154.39 767 


0.77095 


80 


10.15211 


0.22809 


i83. i4io9 


0.79631 



256 



APPENDIX C 

The average benefit realized by a motorist for a time savings or 
the value of motorists time is a function of his trip purpose, income, 
and the amount of time saved. The average benefits generated by the 
program "value of time" algorithm are shown in Tables 68 throuah 72 
for five passenger car trip purposes—work, social -recreational , personal 
business, vacation and school trips. The benefits are shown in dollars 
for eight income ranges by the amount of time saved in minutes. 

The benefits for work and school trips are in dollars per person 
while the benefits for the other trip purposes are in dollars per vehicle, 
The reason for this is that school and work trips are considered to have 
occupants with a range of incomes while personal business, social- 
recreational, and vacation trips are classified as family trips where 
one annual income covers all vehicle occupants. 



257 



Table 68. Benefits of time savings for school 
trips in dollars per person 



Time 






I 


ncome of Motorist 








Saving 






(.thousands of dollars per year) 






(Minutes) 


<4 


4-6 


6-8 


8-10 


10-12 


12-15 


15-20 


>20 


1 


0.000 


0.000 


0.000 


0.000 


0.000 


0.000 


0.000 


0.001 


2 


0.000 


0.000 


0.000 


0.000 


0.000 


0.000 


0.001 


0.001 


3 


0.000 


0.000 


0.000 


0.000 


0.000 


0.000 


0.001 


0.002 


4 


0.000 


0.000 


0.000 


0.000 


0.000 


0.001 


0.001 


0.003 


5 


0.000 


0.000 


0.000 


0.000 


0.000 


0.001 


0.002 


0.003 


6 


0.000 


0.000 


0.000 


0.000 


0.001 


0.002 


0.004 


0.010 


7 


0.000 


0.000 


0.000 


0.001 


0.002 


0.004 


0.012 


0.031 


8 


0.000 


0.000 


0.000 


0.001 


0.003 


0.010 


0.031 


0.082 


9 


0.000 


0.000 


0.001 


0.002 


0.007 


0.024 


0.073 


0.178 


10 


0.000 


0.000 


0.001 


0.003 


0.014 


0.051 


0.150 


0.309 


11 


0.000 


0.000 


0.001 


0.006 


0.027 


0.102 


0.257 


0.452 


12 


0.000 


0.000 


0.002 


0.010 


0.051 


0.178 


0.380 


0.597 


13 


0.000 


0.000 


0.003 


0.018 


0.092 


0.274 


0.507 


0.741 


14 


0.000 


0.001 


0.004 


0.031 


0.150 


0.380 


0.633 


0.884 


15 


0.000 


0.001 


0.007 


0.052 


0.222 


0.488 


0.759 


1.027 


16 


0.000 


0.001 


0.012 


0.083 


0.303 


0.597 


0.885 


1.169 


17 


0.000 


0.002 


0.019 


0.124 


0.390 


0.705 


1.010 


1.312 


18 


0.000 


0.003 


0.029 


0.174 


0.479 


0.813 


1.135 


1.454 


19 


0.000 


0.004 


0.042 


0.233 


0.570 


0.921 


1.260 


1.597 


20 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


21 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


22 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


23 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


24 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


25 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


26 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


27 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


28 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


29 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


30 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


31 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


32 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


33 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


34 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


35 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


36 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


37 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


38 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


39 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 


40 


0.000 


0.006 


0.059 


0.298 


0.660 


1.028 


1.384 


1.739 



258 



Table 69. Benefits of times savings for personal- 
business trips in dollars per vehicle 



Time 






Income of 


Motorist 








Saving 






(thousands of dollars per year) 






(Minutes) 


<4 


4-6 


6-8 


8-10 


10-12 


12-15 


15-20 


>20 


1 


0.000 


0.000 


0.000 


0.000 


0.000 


0.000 


0.001 


0.004 


2 


0.000 


0.000 


0.000 


0.000 


0.000 


0.001 


0.002 


0.007 


3 


0.000 


0.000 


0.000 


0.000 


0.000 


0.001 


0.004 


0.011 


4 


0.000 


0.000 


0.000 


0.000 


0.001 


0.002 


0.005 


0.014 


5 


0.000 


0.000 


0.000 


0.000 


0.001 


0.002 


0.006 


0.018 


6 


0.000 


0.000 


0.000 


0.001 


0.002 


0.007 


0.026 


0.084 


7 


0.000 


0.000 


0.000 


0.001 


0.006 


0.026 


0.100 


0.271 


8 


0.000 


0.000 


0.001 


0.003 


0.018 


0.084 


0.271 


0.543 


9 


0.000 


0.000 


0.001 


0.007 


0.048 


0.213 


0.508 


0.827 


10 


0.000 


0.000 


0.002 


0.018 


0.118 


0.403 


0.756 


1.108 


11 


0.000 


0.000 


0.004 


0.040 


0.241 


0.614 


1.002 


1.387 


12 


0.000 


0.001 


0.007 


0.084 


0.403 


0.827 


1.248 


1.666 


13 


0.000 


0.001 


0.014 


0.161 


0.578 


1.038 


1.492 


1.946 


14 


0.000 


0.001 


0.026 


0.271 


0.756 


1.248 


1.736 


2.225 


15 


0.000 


0.004 


0.056 


0.404 


0.949 


1.478 


2.003 


2.529 


16 


0.001 


0.011 


0.107 


0.554 


1.159 


1.728 


2.293 


2.860 


17 


0.001 


0.020 


0.174 


0.715 


1.369 


1.977 


2.582 


3.190 


18 


0.002 


0.031 


0.256 


0.881 


1.578 


2.225 


2.872 


3.521 


19 


0.003 


0.046 


0.353 


1.049 


1.786 


2.473 


3.161 


3.851 


20 


0.004 


0.065 


0.461 


1.217 


1.993 


2.721 


3.450 


4.182 


21 


0.005 


0.089 


0.578 


1.385 


2.200 


2.969 


3.739 


4.512 


22 


0.006 


0.118 


0.700 


1.552 


2.407 


3.217 


4.028 


4.842 


23 


0.007 


0.155 


0.825 


1.718 


2.613 


3.464 


4.317 


5.173 


24 


0.009 


0.198 


0.951 


1.884 


2.820 


3.712 


4.606 


5.503 


25 


0.010 


0.248 


1.077 


2.050 


3.027 


3.960 


4.895 


5.834 


26 


0.013 


0.305 


1.203 


2.215 


3.233 


4.208 


5.184 


6.164 


27 


0.015 


0.369 


1.328 


2.381 


3.440 


4.456 


5.474 


6.494 


28 


0.018 


0.438 


1.454 


2.546 


3.646 


4.703 


5.763 


6.825 


29 


0.021 


0.512 


1.579 


2.711 


3.853 


4.951 


6.052 


7.155 


30 


0.024 


0.590 


1.704 


2.877 


4.059 


5.199 


6.341 


7.486 


31 


0.024 


0.590 


1.704 


2.877 


4.059 


5.199 


6.341 


7.486 


32 


0.024 


0.590 


1.704 


2.877 


4.059 


5.199 


6.341 


7.486 


33 


0.024 


0.590 


1.704 


2.877 


4.059 


5.199 


6.341 


7.486 


34 


0.024 


0.590 


1.704 


2.877 


4.059 


5.199 


6.341 


7.486 


35 


0.024 


0.590 


1.704 


2.877 


4.059 


5.199 


6.341 


7.486 


36 


0.024 


0.590 


1.704 


2.877 


4.059 


5.199 


6.341 


7.486 


37 


0.024 


0.590 


1.704 


2.877 


4.059 


5.199 


6.341 


7.486 


38 


0.024 


0.590 


1.704 


2.877 


4.059 


5.199 


6.341 


7.486 


39 


0.024 


0.590 


1.704 


2.877 


4.059 


5.199 


6.341 


7.486 


40 


0.024 


0.590 


1.704 


2.877 


4.059 


5.199 


6.341 


7.486 



259 



Table 70. Benefits of time savings for 
social -recreational trips in dollars 
per vehicle 



Time 






I 


ncome of Motorist 








Saving 






(Thousands of dollars pe 


r year) 






(Minutes) 


<4 


4-6 


6-8 


8-10 


10-12 


12-15 


15-20 


>20 


1 


0.000 


0.000 


0.000 


0.001 


0.001 


0.002 


0.005 


0.010 


2 


0.000 


0.000 


0.001 


0.001 


0.002 


0.005 


0.010 


0.020 


3 


0.000 


0.000 


0.001 


0.002 


0.004 


0.007 


0.015 


0.030 


4 


0.000 


0.001 


0.001 


0.002 


0.005 


0.010 


0.020 


0.040 


5 


0.000 


0.001 


0.001 


0.003 


0.006 


0.012 


0.025 


0.049 


6 


0.000 


0.001 


0.002 


0.005 


0.012 


0.029 


0.064 


0.131 


7 


0.000 


0.001 


0.003 


0.009 


0.025 


0.064 


0.145 


0.277 


8 


0.000 


0.002 


0.005 


0.016 


0.049 


0.131 


0.277 


0.466 


9 


0.001 


0.002 


0.008 


0.029 


0.093 


0.235 


0.441 


0.669 


10 


0.001 


0.003 


0.012 


0.049 


0.161 


0.368 


0.618 


0.872 


11 


0.001 


0.004 


0.019 


0.082 


0.255 


0.516 


0.796 


1.073 


12 


0.001 


0.005 


0.029 


0.131 


0.368 


0.669 


0.973 


1.274 


13 


0.001 


0.007 


0.043 


0.196 


0.491 


0.821 


1.148 


1.474 


14 


0.001 


0.009 


0.064 


0.277 


0.618 


0.973 


1.324 


1.674 


15 


0.002 


0.014 


0.087 


0.344 


0.719 


1.097 


1.469 


1.839 


16 


0.003 


0.020 


0.109 


0.392 


0.795 


1.196 


1.585 


1.971 


17 


0.005 


0.027 


0.132 


0.444 


0.874 


1.295 


1.701 


2.103 


18 


0.006 


0.035 


0.158 


0.497 


0.954 


1.394 


1.817 


2.234 


19 


0.007 


0.043 


0.185 


0.554 


1.035 


1.494 


1.932 


2.365 


20 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


21 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


22 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


23 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


24 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


25 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


26 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


27 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


28 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


29 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


30 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


31 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


32 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


33 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


34 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


35 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


36 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


37 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


38 


0.009 


0,052 


0.214 


0.612 


1,117 


1.593 


2.047 


2.496 


39 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 


40 


0.009 


0.052 


0.214 


0.612 


1.117 


1.593 


2.047 


2.496 



260 



Table 71. Benefits of time savings for 
vacation trips in dollars per vehicle 



Time 








Income of Motorist 






Saving 






(Thousands of 


dollars 


per year) 






(Minutes] 


<4 


4-6 


6-8 


8-10 


10-12 


12-15 


15-20 


>20 


1 


0.044 


0.050 


0.057 


0.064 


0.073 


0.082 


0.091 


0.102 


2 


0.087 


0.100 


0.113 


0.129 


0.145 


0.163 


o;i83 


0.203 


3 


0.131 


0.149 


0.170 


0.193 


0.218 


0.245 


0.274 


0.305 


4 


0.174 


0.199 


0.227 


0.257 


0.291 


0.327 


0.365 


0.407 


5 


0.218 


0.249 


0.284 


0.322 


0.363 


0.408 


0.457 


0.509 


6 


0.224 


0.262 


0.306 


0.355 


0.408 


0.467 


0.530 


0.598 


7 


0.230 


0.276 


0.330 


0.390 


0.457 


0.530 


0.609 


0.694 


8 


0.236 


0.291 


0.355 


0.427 


0.509 


0.598 


0.694 


0.796 


9 


0.242 


0.306 


0.381 


0.467 


0.563 


0.669 


0.783 


0.903 


10 


0.249 


0.322 


0.408 


0.509 


0.621 


0.744 


0.875 


0.013 


11 


0.256 


0.338 


0.437 


0.552 


0.681 


0.822 


0.971 


1.126 


12 


0.262 


0.355 


0.467 


0.598 


0.744 


0.903 


1.069 


1.241 


13 


0.269 


0.372 


0.498 


0.645 


0.809 


0.985 


1.169 


1.357 


14 


0.276 


0.390 


0.530 


0.694 


0.875 


1.069 


0.270 


1.474 


15 


0.283 


0.408 


0.562 


0.741 


0.940 


1.150 


1.369 


1.589 


16 


0.291 


0.425 


0.592 


0.787 


1.003 


1.231 


1.466 


1.704 


17 


0.298 


0.442 


0.623 


0.834 


1.067 


1.313 


1.566 


1.819 


18 


0.305 


0.460 


0.655 


0.882 


1.133 


1.396 


1.666 


1.936 


19 


0.312 


0.479 


0.688 


0.932 


1.200 


1.481 


1.767 


2.052 


20 


0.320 


0.497 


0.721 


0.982 


1.268 


1.566 


1.868 


2.170 


21 


0.327 


0.517 


0.755 


1.033 


1.336 


1.652 


1.970 


2.287 


22 


0.335 


0.536 


0.790 


1.085 


1.406 


1.738 


2.073 


2.404 


23 


0.343 


0.556 


0.826 


1.139 


1.477 


1.825 


2.175 


2.522 


24 


0.351 


0.576 


0.862 


1.192 


1.548 


1.903 


2.278 


2.639 


25 


0.358 


0.597 


0.899 


1.247 


1.619 


2.000 


2.380 


2.756 


26 


0.367 


0.618 


0.937 


1.302 


1.691 


2.088 


2.483 


2.873 


27 


0.375 


0.639 


0.975 


1.357 


1.763 


2.176 


2.586 


2.990 


28 


0.383 


0.661 


1.013 


1.413 


1.836 


2.264 


2.688 


3.107 


29 


0.391 


0.683 


1.052 


1.470 


1.909 


2.352 


2.791 


3.223 


30 


0.400 


0.706 


1.092 


1.527 


1.982 


2.440 


2.893 


3.340 


31 


0.400 


0.706 


1.092 


1.527 


1.982 


2.440 


2.893 


3.340 


32 


0.400 


0.706 


1.092 


1.527 


1.982 


2.440 


2.893 


3.340 


33 


0.400 


. 706 


1.092 


1.527 


1.982 


2.440 


2.893 


3.340 


34 


0.400 


0.706 


1.092 


1.527 


1.982 


2.440 


2.893 


3.340 


35 


0.400 


0.706 


1.092 


1.527 


1.982 


2.440 


2.893 


3.340 


36 


0.400 


0.706 


1.092 


1.527 


1.982 


2.440 


2.893 


3.340 


37 


0.400 


0.706 


1.092 


1.527 


1.982 


2.440 


2.893 


3.340 


38 


0.400 


0.706 


1.092 


1.527 


1.982 


2.440 


2.893 


3.340 


39 


0.400 


0.706 


1.092 


1.527 


1.982 


2.440 


2.893 


3.340 


40 


0.400 


0.706 


1.092 


1.527 


1.982 


2.440 


2.893 


3.340 



261 



Table 72. Benefits of time savings for work 
trips in dollars per person 



Time 






I 


ncome of 


Motorist 








Saving 






(Thousa 


nds of dollars pe 


r year) 






(Minutes 


) <4 


4-6 


6-8 


8-10 


10-12 


1-15 


15-20 


>20 


1 


0.001 


0.002 


0.003 


0.004 


0.006 


0.008 


0.011 


0.015 


2 


0.003 


0.004 


0.005 


0.008 


0.011 


0.016 


0.022 


0.031 


3 


0.004 


0.006 


0.008 


0.012 


0.017 


0.024 


0.034 


0.046 


4 


0.005 


0.007 


0.011 


0.016 


0.022 


0.032 


0.045 


0.062 


5 


0.006 


0.009 


0.013 


0.020 


0.028 


0.040 


0.056 


0.077 


6 


0.009 


0.014 


0.022 


0.034 


0.051 


0.076 


0.108 


0.149 


7 


0.013 


0.022 


0.036 


0.058 


0.089 


0.132 


0.186 


0.249 


8 


0.018 


0.033 


0.057 


0.093 


0.145 


0.210 


0.285 


0.365 


9 


0.026 


0.049 


0.086 


0.143 


0.216 


0.302 


0.393 


0.487 


10 


0.036 


0.071 


0.127 


0.205 


0.299 


0.401 


0.505 


0.610 


11 


0.050 


0.100 


0.177 


0.276 


0.387 


0.502 


0.618 


0.732 


12 


0.068 


0.137 


0.236 


0.354 


0.478 


0.604 


0.729 


0.854 


13 


0.091 


0.180 


0.300 


0.434 


0.570 


0.706 


0.841 


0.975 


14 


0.119 


0.230 


0.368 


0.514 


0.661 


0.807 


0.952 


1.096 


15 


0.137 


0.263 


0.413 


0.570 


0.728 


0.883 


1.037 


0.191 


16 


0.142 


0.274 


0.434 


0.602 


0.769 


0.934 


1.098 


1.261 


17 


0.146 


0.286 


0.456 


0.633 


0.811 


0.986 


1.159 


1.331 


18 


0.151 


0.298 


0.477 


0.666 


0.853 


1.038 


0.220 


1.401 


19 


0.155 


0.311 


0.500 


0.698 


0.896 


1.090 


1.281 


1.470 


20 


0.160 


0.323 


0.522 


0,731 


0.939 


1.132 


1.342 


1.540 


21 


0.165 


0.336 


0.545 


0.765 


0.982 


1.195 


1.403 


1.609 


22 


0.169 


0.349 


0.569 


0.798 


1.026 


1.247 


1.464 


1.678 


23 


0.174 


0.363 


0.592 


0.832 


1.069 


1.299 


1.525 


1.748 


24 


0.179 


0.376 


0.616 


0.866 


1.112 


1.352 


1.586 


1.817 


25 


0.184 


0.390 


0.640 


0.901 


1.156 


1.404 


1.646 


1.886 


26 


0.189 


0.404 


0.665 


0.935 


1.199 


1.456 


1.707 


1.955 


27 


0.195 


0.418 


0.689 


0.969 


1.243 


1.508 


1.767 


2.024 


28 


0.200 


0.432 


0.714 


1.004 


1.286 


1.560 


1.828 


2.092 


29 


0.205 


0.447 


0.739 


1.039 


1.330 


1.612 


1.888 


2.161 


30 


0.210 


0.462 


0.764 


1.073 


1.373 


1.664 


1.958 


2.230 


31 


0.216 


0.477 


0.789 


1.108 


1.417 


1.715 


2.008 


2.299 


32 


0.221 


0.492 


0.815 


1.143 


1.460 


1.767 


2.069 


2.367 


33 


0.227 


0.507 


0.840 


1.177 


1.503 


1.819 


2.129 


2.436 


34 


0.232 


0.522 


0.866 


1.212 


1.546 


1.871 


2.189 


2.505 


35 


0.238 


0.538 


0.891 


1.247 


1.590 


1.922 


2.249 


2.573 


36 


0.244 


0.553 


0.917 


1.281 


1.633 


1.974 


2.309 


2.642 


37 


0.249 


0.569 


0.943 


1.316 


1.676 


2.025 


2.369 


2.710 


38 


0.255 


0.585 


0.968 


1.351 


1.719 


2.077 


2.429 


2.779 


39 


0.261 


0.601 


0.994 


1.385 


1.762 


2.128 


2.489 


2.848 


40 


0.267 


0.617 


1.020 


1.420 


1.805 


2.180 


2.549 


2.916 



262 



APPENDIX D 
Glossary 



Activity 



Activity Workload 



Available Occupancy Hours - 



Closure Category 



Directional Lanes 



Influence Zone 



Lane Closure 



Maintenance Level 



A specific work function which is performed 
on the pavement, i.e., pavement patching, 
resurfacing, joint sealing, etc. 

The quantifiable units of work generated for 
a work activity, e.g., square yards of patch- 
ing, linear feet of crack sealing, lane 
miles of resurfacing, etc. 

The hours of a day when work crews are per- 
mitted to occupy a roadway. 

A variety of lane closure sequences can be 
used in the delineation of work zone for 
activity work crews. Each closure sequence 
is defined as a closure category. As an 
example, on an eight-lane freeway, the follow- 
ing six sequences of closure categories are 
feasible. 

1. Close one lane at a time 

2. Close two lanes at a time 

3. Close three, then one lane 

4. Close all lanes and use shoulder 

5. Close all lanes and use detour 

6. Close all lanes and cross traffic 

over to opposite lanes 

The number of lanes going in a single direc- 
tion for a given freeway, i.e., on an eight- 
lane freeway, there are four lanes in one 
direction. 

The distance over which vehicles are operated 
at an average reduced speed due to lane 
closures on the freeway. 

The number of directional lanes closed for 
a work activity, i.e., lane closure 1 is 
one lane closed, lane closure 2 is two lanes 
closed, etc. 

The number of periods in a year when the work- 
load generated by a roadway will be taken care 
of. If 100 square yards of patching were the 



263 



Maintenance 
(Cont.) 



Level 



Occupancy Interval 



Occupancy Period 



Pavement Analysis Age 



annual workload, then a maintenance level 
of one would mean that the road was occu- 
pied for one period to perform the annual 
work, i.e., work crews would be sent to 
the road every day until the total work- 
load generated by the roadway had been 
taken care of by the work crews. A main- 
tenance level of Two would mean that at 
two periods in the year, the roadway would 
be occupied to perform work. Further, 
only one-half of the annual workload would 
be available during each period. Finally, 
if the maintenance level were .2, then 
the road would only be occupied every 
fifth year. The workload generated each 
year would be continually accumulated 
until it could be taken care of in the 
fifth year. 

Any continuous interval of time when the 
roadway can be occupied which is less than 
or equal to 24 hours. As an example, one 
occupancy interval could be a roadway 
occupancy which started at 8 A.M. and was 
terminated at 3 P.M. If crews reoccupied 
the road at 8 P.M. and stayed until 11 P.M. 
that would be a second occupancy interval. 

A period of time when work crews occupy a 
roadway on a continual basis, i.e., at 
every occupancy interval opportunity. 
Where the maintenance level is greater than 
one, Tor example 3, the annual workload 
is divided into three parts. It requires 
an occupancy period to complete the work- 
load for each of the three parts. 

The models predicting maintenance workload 
are a function c c pavement age. A pavement 
deteriorates due to loadings and fails at 
a rate related to its design life. The 
workload models are based on a deteriora- 
tion of the pavement over twenty years. 
The pavement analysis age is created for 
use in the workload models to accommodate 
axle loads and a design life which do not 
correspond to the twenty -year life asso- 
ciated with the models. 



264 



Pollution Day 



Simulation Workload 



The total emissions of CO and HC genera- 
ted by vehicles operating normally on a 
freeway of a given length during a 24- 
hour period. The increase in emissions 
created during a roadway occupancy are 
converted into pollution days which 
therefore represent the days of normal 
operation required to generate the in- 
creased emissions caused by the roadway 
occupancy. 

The total units of work performed during 
the simulation process in subroutine 
MAINT. The simulation workload is con- 
trolled by the worksite workload and the 
number of iterations specified for the 
simulation. 



Worksite 
Work Zone 



The spot location on the roadway where 
work crews perform productive work. 

The area on a roadway where work crews 
can actually perform work. The length 
of this zone does not include the cone 
taper used to channel traffic. 



265 



APPENDIX E 
SELECTED BIBLIOGRAPHY 



Abramson, P., "An Accident Evaluation Analysis." Paper presented at 
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Agnello, Richard J., "Measuring Time Losses at Highway Bottlenecks 
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Research Record No. 467, 1973, p. 60. 

Alexander, J. A. and Moavenzadeh, F., "Highway Maintenance." Sponsored 
by Urban Systems Laboratory, TR-70-38, September 1970 

Ayanian, H., "An example of Reducation of Highway Capacity Caused 
by Construction Activities Adjacent to the Freeway Traveled Way." 
Freeway Operation Department Report No. 70-7, California Transportation 
Agency Department of Public Works, June 1970 

Bleck, A. T., "Pavements and Influences Affecting or Determining Their 
Performance." Highway Research Board Bulletin No. 20, pp. 21-70. 

Bleyl, Robert L., "Speed Profiles Approaching a Traffic Signal." 
Highway Research Board Record Number 384, 1972. 

Brown, James L., "The Texas Highway Department Pavement Management 
System." Paper presented at Highway Research Board Annual Meeting, 
January 1974. 

Burke, Dock, McFarland, W. Frank, "Accident Costs: Some Estimates for 
Use in Engineering Economy Studies." Highway Research Record 467, 
1973, p. 66. 

Cirillo, Julie Anna, "The Relationship of Accidents to Length of 
Speed-Change Lanes and Weaving Areas on Interstate Highways." 
Highway Research Record 312, 1970. 

Courage, Kenneth G., Bissell, Howard H., "Recording and Analysis of 
Traffic Engineering Measures." Highway Research Record No. 398, 1972, 
p. 2. 

Courage, Kenneth G., "Some Electronic Measurements of Macroscopic 
Traffic Characteristics on a Multilane Freeway." Highway Research 
Record No. 279, 1969, p. 107. 

Cornette, Don, "Operational Characteristics of Lane Drops." NTIS 
Publication No. 215-535, August 1972. 

Crowther, R. F., "A Study of Sampling Error in Spot and Travel Speed," 
Department of Police Administration, Indiana University, December 1964. 
FHWA Library, TEA 260 169 

266 



Dart, Olin K., Jr., and Mann, Lawrence, Jr., "Relationship of Rural 
Highway Geometry to Accident Rates in Louisiana." Highway Research 
Record 312, 1970, p. 16. 

Darter, Michael I., Hudson, W. Ronald, and Haas, Ralph C. G., "Selection 
of Optimal Pavement Designs Considering Reliability, Performance, and 
Costs." Paper presented at 53rd Annual Meeting of Highway Research 
Board, January 1974. 

Drake, Joseph S., Schofer, Joseph L., May, Adolf D. Jr., "A Statistical 
Analysis of Speed Density Hypotheses." Highway Research Record No. 154, 
1967. 

Duckstein, Lucien, "Control of Traffic in Tunnels to Maximize Flow," 
Highway Research Record No. 154, 1967, p. 1. 

Dudek, Conrad L., Messer, Carroll J., Friebele, John D., "Method for 
Predicting Travel Time and Other Operational Measures in Real-time 
During Freeway Incident Conditions." Highway Research Record No. 461, 
1973, p. 1. 

Dudek, Conrad L., Messer, Carroll J., Loutzenheiser, Roy C, "A Systems 
Analysis for a Real-time Freeway Traffic Information System for the 
Inbound Gulf Freeway Corridor." Texas Transportation Institute, 
Research Report 139-5, Study 2-8069-139, 1971. 

Findakly, Hani, Moavenzadeh, Fred, Soussou, Joseph, "Stochastic Model 
for Analysis of Pavement Systems." Transportation Engineering Journal 
of ASCE, Volume 100, No. TE1, February 1974, p. 57 

Forbes, C. E., "Reducing Motorist Inconvenience Due to Maintenance 
Operations on High-Volume Freeways." Speech presented at Highway 
Research Board Western Summer Meeting, Sacramento, August, 1970. 

Gafarian, A. V., Lawrence, R. L., and Munjal , P. K., "An Experimental 
Validation of Various Methods for Obtaining Relationships Between 
Traffic Flow, Concentration, and Speed on Multilane Highways." 
Highway Research Record No. 349, 1971, p. 13. 

Goodwin, Browne C, Lawrence, Robert L., "Investigation of Lane Drops." 
Highway Research Record No. 388, 1972, P. 45. 

Gordinier, D. E., Chamberlin, William P., "Pressure Relief Joints for 
Rigid Pavements." Research Report 68-12, Engineering Research and 
Development Bureau, New York State Department of Transportation, 
February 1969. 

Haas, Ralph, "General Concepts of Systems Analysis as Applied to 
Pavements." Paper presented at Annual Meeting, Highway Research- 
Board, Washington, D. C, January 1974. 

2 67 



Havens, J. H., Rahal , A., "Expansive Limestone Aggregate in a Concrete 
Pavement." Kentucky Department of Highways, Division of Research, 
Research Report 325, April 1972. 

Head, J. A., "Predicting Traffic Accidents from Roadway Elements on 
Urban Extensions of State Highways." Highway Research Bulletin No. 208, 
1959, p. 45. 

Henry, Robert L., "Final Report on a Study of Control of Pavement 
Movements Adjacent to Structures." Research Project for the Mississippi 
State Highway Department by the University of Mississippi, Engineering 
Experiment Station, February 15, 1968. 

Hejal , S. S., Yoder, S. R., Oppenlander, J. C, "Optimal Design of 
Flexible Pavement Sections," Highway Research Board Record No. 337, 
1970. 

Hillegas, Barry D., Houghton, Donald G., Athol , Patrick J., "An 
Investigation of Flow-Density Discontinuity and Dual -Mode Traffic 
Behavior." 

Hoi brook, Lawrence, "Probability Model for Joint Deterioration." 
Highway Research Record 471, 1973, p. 118. 

Housel , William S., "Evaluation of Pavement Performance Related to 
Design, Construction, Maintenance and Operation." Hiqhway Research 
Record, No. 46, 1964, p. 135. 

Hull, E. M. , "A Comparison of Delay to Vehicles Crossing Urban Inter- 
sections Four-way Stop U. S. Semi -Traffic-Actuated Signal Control." 
Student Research Report, ITTE, University of California, Berkeley, No. 4 
January 1952, FHWA Library, TEA 1014 C2174 No. 4 C.2 

Kahn, David and Mintz, Ronald, "Freeway Traffic Flow Following a Lane 
Blockage." Federal Highway Administration Report No. DOT-TSC-FHWA- 
73-1, NTIS Publication No. PB 222 399, 1973. 

Kasianchuk, D. A., Moni smith, C. L., and Garrison, W. A., "Asphalt 
Concrete Pavement Design--a Subsystem to Consider the Fatigue Mode of 
Distress." Highway Research Record, No. 291, 1969, pp. 159-172. 

Kher, Ramesh K. , Hudson, W. Ronald and McCullough, B. Frank, "A 
Systems Analysis of Rigid Pavement Design." Research Report Number 
123-5, Texas Transportation Institute, January 1971. 

Konder, Robert L and Krizek, Raymond J., "Factors Influencing Flexible 
Pavement Performance." National Cooperative Highway Research Program 
Report No. 22, 1966, 69 pp. 

268 



Lundy, Richard A., "Effect of Traffic Volumes and Number of Lanes 
On Freeway Accident Rates." Highway Research Record No. 99, 1965, 
p. 138 

Mann, Lawrence, Jr., "Predicting Highway Maintenance Costs." 

Makigami, Yasuji and Woodie, William L., "Freeway Travel Time 
Evaluation Technique." Highway Research Record No. 321, 1970 

Marcel les, J. C, "An Economic Evaluation of Traffic Movement at 
Various Speeds." Highway Research Record, No. 35, pp. 18-40, 1963. 

Martin, Darryl B., and Newman, Leonard, "Evaluation of Freeway Traffic 
Flow at Ramps, Collector Roads, and Lane Drops." Highway Research 
Record No. 432, 1973, p. 25. 

May, Adolf D. , Jr., and Keller, E. M., "Non-Integer Car-Following 
Models." Highway Research Record No. 199, 1967, p. 19 

McCul lough, B. G., and Moni smith, C. L., "A Pavement Overlay Design 
System Considering Wheel Loads, Temperature Changes, and Performance." 
Highway Research Record 327, 1970, p. 64. 

Mika, H. S., Kreer, J. B., Yuan, L. S., "Dual Mode Behavior of Freeway 
Traffic." Highway Research Record No. 279, 1969, p. 1. 

Mikhalkin, Basil, Payne, Harold J., Isaksen, Leif, "Estimation of 
Speed from Presence Detectors." Highway Research Record 388, 1972, 
p. 73. 

Munjal , P. K., Hsu, Y. S., Carpenter, R., "Experimental Validation of 
Modified Boltzmann Type of Model and Shift Model for Multilane Traffic 
Flow." Highway Research Record 409, 1972, p. 1. 

Oehler, L. T. , Holbrook, L. F., "Performance of Michigan's Postwar 
Concrete Pavement." Michigan State Highway Commission, Research 
Laboratory Section, Research Report R-711, Research Project 39 F-7( 15) 
June 1970.. 

Oppenlander, J. C, "Sample Size Determination for Spot-Speed Studies 
at Rural, Intermediate, and Urban Locations," Highway Research Record 
No. 35, pp. 78-80, 1963 

Oppenlander, J. C, "Sample Size Requirements for Vehicular Speed 
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Paddock, Richard D., "The Traffic Conflicts Technique: An Accident 
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Washington, D. C. , January 1974. 

269 



Parman, William J., "A Pilot Study of Maintenance Costs of Idaho 
Highways," Research Report 1, March 1965, University of Idaho. 

Parsonson, Peter S., "A System to Monitor the Road-User Cost of 
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P. 1. 

Payne, Harold J., <Freeway Traffic Control and Surveillance Model." 
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1973, p. 767. 

Price, H. 0., "The Effect on Vehicle Speeds of a Speed Zone Ahead 
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Report, June 1951. FHWA Library TEA-1014 C2174 No. 1 

Rand, David W., "Pavement Evaluation III." NTIS Report No. PB 225 600, 
August 1973. 

Reagel , F. V., Gotham, D. E., Yeoman, R. C, "Field Observations on 
Effects of Joints on Cracking and Other Deterioration in Concrete 
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Reilly, Eugene F. , Seifer, Joseph, "Truck Equivalency." Highway Research 
Record 289, 1969, p. 25 

R0rbech, Jens, "Capacity and Level of Service Conditions on Danish 
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2 70 



Tracy, J. L., "Effect of Illumination on Operating Characteristics of 
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272 



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